Understanding image sharpness:
Digital cameras vs. film, part 1
by Norman Koren

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Table of contents

for the
image sharpness
series

Part 1: Introduction
Part 1A: Film and lenses
Part 2: Scanners and sharpening
4000 vs. 8000 dpi scans
Part 3: Printers and prints
Part 4: Epson 1270 results
Part 5: Lens testing
Part 6: Depth of field and diffraction
Part 8: Grain and sharpness: comparisons
Digital cameras vs. film, part 1
Introduction | Digital image quality overview
Digital image sensors | Simulations | Resolution summary
Digital cameras vs. film, part 2
Dennis Wilkins' tests
The future of digital cameras | Links
Information theory and image quality
MTF from Dpreview.com data
Preface, September 17, 2005. Most of the text that follows was written in 2002 and 2003, before I purchased my first digital SLR (the Canon EOS-10D in March 2003; since replaced by the EOS-20D). Since July 2003 I've been intensively involved in developing the Imatest program for measuring image quality in cameras, lenses, scanners and printers. I haven't been able to keep this page up-to-date, but I'll update it somewhat in the next few days.
In Digital cameras vs. film, parts 1 and 2, we use the tools developed in earlier in the series to compare digital and film cameras, and we address the question, "How many pixels does a digital sensor need to outperform 35mm film?" The answer is less speculative than it used to be: The 11+ megapixel Canon EOS-1Ds, EOS-1Ds Mark II, and EOS 5D clearly outperform 35mm. I can make finer prints with the 8.3 megapixel EOS 20D (razor sharp at 13x19 inches) than I ever could with 35mm— and I was fanatic about lenses and darkroom work. We also look at the rapid advances of digital sensor technology, which have made some digital cameras obsolete in a matter of months. The good news is that the advances are slowing down-- digital cameras are stabilizing and it has become safe to buy one without fear of rapid obsolescence (though obsolescence will still happen; just slower).

Part 1 describes the four pillars of image quality, digital image sensors, the simulation technique, and presents a summary of results comparing digital camera resolution with film. Part 2 contains Dennis Wilkins' comparison of the Nikon D100 with film, my view of the future of digital cameras, Links, a discussion of Information theory and image quality, and how to measure MTF from Dpreview.com test results. I can't keep up with all the latest camera models. Sites with the latest news and reviews are listed in Digital cameras: Links. Digital camera sharpness measurements are available on Imatest sharpness comparisons.

If you are unfamiliar with MTF, you may want to review Part 1 of this series.

Related pages: The Canon EOS-10D Digital SLR | Digital cameras | Tonal quality and dynamic range in digital cameras
Digital cameras vs. film, part 2 | Dennis Wilkins' tests | The future of digital cameras | Links
Information theory and image quality | MTF from Dpreview.com test results

Green is for geeks. Do you get excited by an elegant equation? Were you passionate about your college math classes? Then you're probably a math geek-- a member of a maligned and misunderstood but highly elite fellowship. The text in green is for you. If you're normal or mathematically challenged, you may skip these sections. You'll never know what you missed.
 
September 2004 I've released Imatest: a program for testing digital image sharpness and quality using simple widely available targets.
February 2004 I've updated the simulations to reflect my experience with the Canon EOS 10D. Digital cameras come off slightly better in the comparisions. The 10D has about 80% of the resolution of 35mm film in both the simulations and my tests. But resolution isn't the only factor that contributes to image quality. Noise (the counterpart of grain in digital cameras) is nearly absent in the 10D.
November 2003 I've written a new page, Tonal quality and dynamic range in digital cameras, that shows how to obtain optimum tonal quality from your digital camera and how to take advantage of its hidden dynamic range.
June 2003 I put up a comparison between the Nikon D100 digital and N70 film cameras, performed by Dennis Wilkins.
May 2003 I purchased a Canon EOS 10D digital SLR and put up a page on it.

Thanks to Miles Hecker for his valuable critiques and guidance.

Thanks to Alex Tutubalin for pointing out some errors-- painful, but this page is better as a result.

Introduction

Canon EOS D60I became interested in the question, "How many pixels does it take for a digital sensor to outperform 35mm film?," after I read a rave review of the 3.1 megapixel Canon EOS-D30, written in late 2000 by Michael Reichmann of Luminous-Landscape.com. At $3,000, the D30 was the first "affordable" digital SLR (DSLR), accepting Canon's line of EF lenses. It was followed by the $2,200 6.3-megapixel EOS-D60 in February 2002, the $1,500 6.3-megapixel EOS 10D in March 2003, and the $1,500 8.2-megapixel EOS-20D in September 2004.

In September 2002 two full-frame digital cameras were announced: The 11 Megapixel Canon EOS-1Ds and the 14 Megapixel Kodak DCS Pro 14n. These cameras outperform 35mm film, winning the race as much on low noise (absence of grain-- far superior to 35mm) as resolution. The Canon EOS-1Ds Mark II, announced in September 2004, challenges medium format film, and the Canon EOS 5D, announced in August 2005 drops the price of a full-frame 12.8 megapixel SLR to $3,300 USD, not much more than the old 3 megapixel EOS-D30.

This is exciting news because of the many advantages of digital cameras: First of all there is no film, which is the primary factor limiting resolution in the 35mm format. There is very little noise (the digital counterpart of grain) in sensors with pixel spacings larger than about 6 microns. There are no problems with film flatness, inconsistent development, or scanners. You can preview your image immediately-- no trips to the camera shop to drop off film and pick it up, and no worry about airport x-rays.

The four pillars of digital camera image quality-- an overview

Four major factors contribute to digital camera image quality.
All of these properties can be measured with Imatest, a program that measures digital image sharpness and quality using simple, widely available targets. Resolution (MTF) is measured by SFR with a target you can print yourself. Noise and dynamic range is measured by Q-13 Stepchart. Color quality is measured by Colorcheck

Digital image sensors

The key geometrical specifications of digital sensors are sensor size, pixel spacing, and the number of pixels (horizontal h, vertical v, and total hxv. These specifications are discussed in detail in my page on Digital cameras. Sensor and pixel size issued are discussed below.
.
 Pixel size, sensor size, pixel count, and image quality
Pixel count (8 Megapixels, wow!) grabs our attention in digital camera specifications. But it doesn't tell everything. Pixel and sensor size matters. It turns out there is an optimum range for pixel size and an advantage to large (i.e., costly) sensors. For reference, sensor diagonal measurements are 43.3 mm for full frame 35mm film; up to 11 mm for compact digital cameras, and 22 mm and over for digital SLRs.
  • Small pixels have excellent resolution but suffer from increased noise (hence poorer signal-to-noise ratio, SNR), reduced exposure range (fewer f-stops), and reduced sensitivity (lower ISO speed). The reason is simple: they respond to fewer photons and can hold fewer electrons. These effects are most noticeable in compact digital cameras, which have pixels smaller than 4 µm. The exact relationship between noise and pixel size is difficult to quantify since there are several noise mechanisms, each of which scales differently.
  • Large pixels have good SNR, ISO speed and exposure range, but suffer from aliasing-- low spatial frequency artifacts that appear when the lens has significant response above the Nyquist frequency: 1/(2*pixel spacing). Aliasing typically manifests as Moiré patterns on images with high frequency repetitive patterns, such as window screens and fabrics. It can be reduced by anti-aliasing (low pass) filters, which are expensive and unavoidably reduce resolution. In Optics for digital photography from Schneider Optics, the author states that aliasing will be adequately controlled if the MTF of the lens + sensor at Nyquist is no more than about 10%. Compact digital cameras, which have pixels smaller than 4 µm, don't need anti-aliasing filters: the lens is sufficient. This helps control cost.
  • Small sensors run into problems with lens diffraction, which limits image resolution at small apertures-- starting around f/16 for the 35mm format. At large apertures-- f/4 and above-- resolution is limited by aberrations. There is a resolution "sweet spot" between the two limits, typically between f/5.6 and f/11 for good 35mm lenses. The aperture at which a lens becomes diffraction-limited is proportional to the format size: 22 mm diagonal sensors become diffraction-limited at f/8 and 11 mm diagonal sensors become diffraction-limited at f/4-- the same aperture where it becomes aberration-limited. There is little "sweet spot;" the total image resolution at optimum aperture is less than for larger formats. Of course cameras with small sensors can be made very compact, which is attractive to consumers.
  • Large sensors cost more. No getting around it. That's the major reason compact digital cameras are so popular. 11 mm diagonal sensors have 1/16 the area of a 35mm frame. The problem with large sensors is manufacturing yield-- the percentage of sensors that work properly. Suppose an 11 mm sensor has a 90% yield (pretty good). A 44 mm sensor (35mm format; 16x the area) with the same process would have a yield of 0.9016 = 18% (not so hot). Larger sensors tend to have larger pixels, which helps the yield.
Compact digital cameras have sensors with diagonal dimensions between 5 and 11 mm, and pixel pitches 3.4 µm or less. These cameras have acceptably low noise at low ISO speeds and the best of them-- the "prosumer" models-- can make excellent 8½x11 inch or larger prints, depending on pixel count Thanks to noise and diffraction, overall image quality decreases for pixels smaller than 2 µm.

The optimum pixel size for high quality imaging seems to be in the 6-9 µm range. Larger pixels have problems with aliasing and can't take advantage of high quality lenses. Smaller pixels have more noise and less dynamic range and sensitivity. Digital SLRs will stick with 6-9 µm pixels and evolve towards larger sensors with more pixels. 24x36 mm sensors with 16+ megapixels (7.4 µm or less pixel spacing) have performance approaching medium format (see The future of digital cameras), but they won't come cheap for quite some time.

Luminous-landscape.com has two articles on pixel/sensor size: Counting megapixels by Michael Reichmann and Digital camera Image Quality by Miles Hecker.

.
Two technologies are used to manufacture digital sensors: CCD (charge-coupled device: a sort of pixel bucket brigade) and CMOS (complimentary metal oxide semiconductor): a process widely used for computer chips. CCD dominated high quality sensor applications until the Canon EOS D30 was introduced in 2000; CMOS was thought to have intrinsically higher noise. But CMOS has been advancing rapidly; it promises to deliver better performance (including very low noise) and lower power consumption (hence better battery life) at lower cost (CMOS fabrication lines are more widespread and more functions can be integrated on the sensor chip). Canon has a nice site devoted to their CMOS sensor technology.

There are two types of digital sensor: (1) those that use a color filter array (CFA): a filter grid that covers the sensor so that each pixel is sensitive to a single primary color (R, G or B), and (2) sensors that employ the new Foveon X3 technology, where each pixel is sensitive to all three primary colors. Conventional sensors all use CFA's, but Foveon's new technology promises to outperform them if Foveon can deliver.
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Bayer mask sensor patternBayer pattern sensors  Conventional digital sensors have their pixels are arranged as shown on the right, in a pattern known as the Bayer mask (or filter, or mosaic, or CFA for Color Filter Array), with two green pixels for each red and blue pixel. This is appropriate because the eye is most sensitive to green.

With the Bayer mask sensor there is some resolution loss and side effects-- mostly Moiré fringing-- due to interpolation-- the process of filling in the data for the two missing colors at each pixel location. The red and blue pixels are spaced twice as far apart as the green pixels; hence their intrinsic resolution is only half that of green, but sophisticated reconstruction algorithms recover most of the lost resolution as long as some green is present. Interpolation triples the file size (for a given bit depth). For example, in the EOS 10D, a 7 Megapixel RAW file (one pixel per color, bit depth=12, losslessly compressed) is transformed into a 18.9 Megabyte 24-bit file (8 bits per color, which sacrifices some tonal detail) or an 37.8 Megabyte 48-bit file (16 bits per color; which keeps the full tonal detail). (It's always better to edit in 48 bits, but it's OK to store the file in 24 bits once editing is complete.)

You may think of interpolation as the miracle of the multiplication of the pixels. [The Cornell University DSP (Digital Signal Processing) Lab has a strong interest in image interpolation. The highly technical paper, Reconstruction of Color Images from CCD Arrays, by D. D. Muresan, Steve Luke, and T. W. Parks is of particular interest.]

The best interpolation algorithms are iterative-- they are extremely computationally intensive; hence they are best performed on RAW image files in a computer. In-camera interpolation algorithms are less effective and more subject to artifacts such as Moiré.
Foveon's X3 sensors  Announced in February 2002, represents a real breakthrough in digital sensor technology. DPreview.com has a description of the technology and full review of the 3.4 megapixel Sigma SD9 SLR. The X3 senses all three colors at each pixel position. No Bayer interpolation is needed. It apparently doesn't need an anti-aliasing filter because its monochrome aliasing (Moiré fringing) is far less visible than the colored aliasing in Bayer sensors. Its MTF is very high around the Nyquist frequency-- enough to cause disaster with Bayer sensors. Using MTF as a measure of resolution, it meets the claim of doubling image resolution. Mike Chaney, author of Qimage Pro, has performed a simulation comparing a prototype Foveon sensor with a Bayer sensor by "Bayerizing" the Foveon pixels in a Foveon image (filtering them red, green, or blue), then reconstructing the image using a realistic algorithm. He did this without and with anti-aliasing filters. His results confirm a 25% gain for the black and white test pattern, but the gap between Foveon and Bayer sensors is greater for patterns that lack green. Patterns were red and blue dominate look worse with Bayer sensors. Foveon has a nice paper on the MTF of its sensors.

The 3.4 megapixel Sigma SD9 SLR camera body, reviewed by dpreview.com and photo.net, only takes Sigma lenses. It faces tough competition from 6 megapixel Canon and Nikon bodies, that many photographers can use with their existing lenses. A tough sell but a promising future. [To learn more about the technology, check out US patent 5,965,875-- not easy reading.]

The Fujifilm S2 Pro is a Nikon-mount DSLR with a 6.17 megapixel "Super CCD" that produces up to 12.1 Million (4256x2848) interpolated pixels. Price is $1996 US. (Jauary 2004) I'm not sure how to simulate it. DPReview.com has the URLs of two Japanese sites with sample images: Miscall and Yamada Kumio. It's well worth comparing the ISO 100 images from the EOS D60, D100, and S2 Pro on Kumio's site. Note particularly the block wall just below the clock. The S2 Pro is clearly superior; the S2 images on both sites are amazing. Imaging-resouce and Dpreview.com have published very positive reviews; resoluton is clearly superior the the D60 and D100. The S2 Pro may well equal 35mm.

The S2 Pro uses interpolation trickery to double the number of pixels. The idea is that the eye is more sensitive to horizontal and vertical detail than to diagonal detail. Vertical and horizontal detail also tends to be more prevalent in scenes. By arranging pixels diagonally, the horizontal and vertical spacing is reduced by a factor of the square root of 2 (0.7071x). Interpolation takes place not only at pixel locations, but between them, doubling the number of pixels and improving the interpolated vertical and horizontal resolution. The octagonal pixels are said to be a better match for the microlens used to increase the sensor's effective fill factor.

Strange, but it seems to work. This excellent post sheds light on how.

Simulation technique

We use the MTFcurve2 program to evaluate the performance of current and future cameras. MTFcurve2 calculates the spatial frequency response (the MTF) of each component (lens, film, sensor, etc.), and calculates the total system MTF.

The key parameter required to model a digital camera is the sensor's MTF response. Solid data on sensor MTF is extremely hard to find on the Web. This forces us to make assumptions-- to choose models that match test results. As we mentioned in Part 2, the response of scanners and sensors can be approximated by functions of the form |sinc(f/dscan)|n, where dscan is sensor resolution in pixels/mm.

These functions are simple, have nulls at the correct frequencies, and closely approximate measured data. Their frequency and spatial response is shown in graphs in Part 2 for n = 1 through 4. The spatial sensitivity function for sinc(f/dscan) is a rectangle of length 1/dscan (the length of a sensor element with a fill factor of 1). An "ideal" rectangular sensor with a 100% fill factor would have a sinc(f/dscan) response. For n > 1, the spatial sensitivity is the rectangle convolved with itself (n-1) times. For sinc2 it is a triangle of length 2/dscan. As n increases, spatial response spreads.
We select values of n for |sinc(f/dscan)|n that yield results similar to available data. Diagnostics for Digital Capture using MTF by Don Williams of Eastman Kodak contains an MTF plot for three digital cameras (Figure 2), one with evident sharpening. MTF for digital cameras tested by www.dpreview.com can be estimated with the procedure outlined below.

The MTF of CCD digital sensors is affected by diffusion or "blooming" between pixels. Most digital sensors have anti-aliasing (lowpass) filters, which spread spatial response and reduce high frequency MTF. Bayer sensors have some MTF loss due to their layout and interpolation routines, though sophisticated software keeps this loss to a minumum. Hence no digital camera sensors would be expected to match the sinc(f/dscan) response of an ideal rectangular sensor. After some trial-and-error the following approximations were selected. [I changed the assumptions February 2, 2004 to conform to my experience with the Canon EOS 10D. Digital cameras come out better as a result.]

Since digital cameras have varying amounts of sharpening, which strongly affects the 50% MTF frequency, we apply consistent sharpening to the simulations. We compare digital camera resolution with Provia film scanned at 4000 dpi and sharpened. This provides a fair comparison because it contains nearly all the information on the film-- a sharpened 4000 dpi scan results in a sharper image than you can get through an enlarging lens.
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Here are the results for the 135 pixel/mm Canon EOS 10D (and 300D) with the "excellent" lens, sharpened with ksharp = 0.50 (generated by MTFcurve2 1e4 0 61 2 135 3 .50). The 50% and 10% MTF frequencies are 61 and 84 line pairs/mm, considerably higher than Provia scanned at 4000 dpi and sharpened with ksharp = 0.60 (46.7 and 75.6 lp/mm). There is little aliasing (response above the Nyquist frequency, 67.5 lp/mm).

The key result is the black line: the MTF of the lens + sensor + sharpening.

The thin magenta curve is the spatial response of the lens only. The kinky red curve is the spatial response of the sharpened digital image. The thin blue line is the MTF of the lens. The blue dashed line is the MTF of the sensor + sharpening.
The sensor has a built-in anti-aliasing (low pass) filter. These numbers are consistent with DPReview's resolution chart comparisons.

Since the 10D's sensor dimensions are 15.1/24 = 0.63 as large as 35mm, the total resolution at the 50% level is (61/46.7) * (15.1/24) = 0.82 that of 35mm 4000 dpi Provia. That's fairly close, and when you consider the extremely low noise of the digital sensor-- the absence of grain (see the discussion on information theory), overall image quality approaches that of 35mm. Another advantage of the low noise is that you can get away with more sharpening.

Canon EOS D30 MTF (sharpened)
The EOS 10D has 82% the total resolution of full frame 35mm Provia scanned at 4000 dpi.
But perceived image quality approaches that of film because of the low noise-- the absence grain.
Simulations of the Foveon X3 sensor assuming a |sinc(f/dscan)|1.5 response indicates that a 105 pixel/mm sensor would have the same 50% MTF frequency as the 135 pixel/mm EOS 10D. On this basis I estimate that the linear resolution of the Foveon X3 in a camera is about 25 to 28% higher than a conventional sensor with the same pixel spacing. Based on resolution only, the X3 sensor would have the same image quality as a conventional sensor with approximately 1.6x as many pixels. But since the X3 has greatly reduced artifacts (Moiré, etc.), I'd guess the advantage would be about 1.8x, i.e., the 3.4 megapixel Foveon X3 sensor in the Sigma SD9/SD10 would equal a conventional Bayer sensor with 6.1 megapixels-- almost equal to the Canon EOS 10D and Nikon D100. (I suspect that the severe Moiré in the photo.net SD9 preview is at least partially the result of an inferior Bayer interpolation routine.)

Digital camera resolution summary

Here is where we take advantage of the predictive power of the MTFcurve2 program. The tables below summarize the simulated resolution of several digital cameras. Because of their low noise, which allows greater sharpening, many people will find digital cameras to be sharper than the numbers indicated here. The table below is not comprehensive. I omitted cameras like the Fuji S2 Pro, whose interpolated Super CCD response is difficult to simulate.
The measured resolution of several digital cameras can be found in Sharpness comparisons on the Imatest website. Imatest is a software package that allows you to measure lens sharpness and digital camera performance using inexpensive easily-available targets.  The comparisons between cameras are similar to those presented below, but the absolute values are different because a sharpening radius of 2 (vs. 1 here) is used in the analysis.

Camera[1,2] Sensor
size mm
(diag.)
Pixel array
(total
Mpxls)
Pixel
spacing
(µm)
MTF [3]
lp/mm
50%/10%
Resolution
relative to
35mm [4,5]
approx.
cost
(US$)
Comments
Fuji Provia 100F, excellent lens, 4000 dpi scan, sharpened 36x24
(43.3)
3779x5669
(21.4)
6.35
(scanner)
46.7 / 75.6
[3A]
(1.0) --- The benchmark for high quality 35mm color slide film. Similar resolution to 10.2 µm Bayer sensor pixels (with anti-aliasing). s = 0.25. [6]
Digital SLRs (DSLRs)
Canon EOS D30
(discontinued)
22.7x15.1
(27.3)
2160x1440
(3.11)
10.2 46 / 63 0.62 3000 (at intro, autumn 2000) CMOS sensor. s = 0.44.
Canon EOS 10D
Canon EOS 300D
22.7x15.1
(27.3)
3072x2048
(6.3)
7.4 61 / 84 0.82 1499 Replaced the 6.3 megapixel D60. Its CMOS sensor has lower noise. ISO 100-3200. 790 g. body. s = 0.50 IR
Canon EOS-1D 28.7x19.1
(34.5)
2496x1662
(4.15)
11.5 43.2 / 57.3 0.74 4000 To be
discontinued
Larger sensor than D60. SO 200-1600. Large, heavy (1250 g.) professional body. s = 0.48.
Canon EOS-1D
Mark II
28.7x19.1
(34.5)
3504x2336
(8.2)
8.43 55.7 / 75.4 0.95 4500 Replacement for 1D, early 2004. Optimized for speed. s = 0.50.  RG
Canon EOS-1Ds 35.8x23.8
(43.0)
4064x2704
(11.0)
8.8 54, 72.7 1.16 7999
LL's comments
Announced Sept. 2002. 1265 g (heavy). s = 0.50.  Sample images from Canon | LL | IR | RG.
Kodak DCS Pro 14n 36x24
(43.3)
4536x3024
(13.7)
7.9 66.4 / 88.7 1.42 5000 To be
discontinued?
Announced Sept. 2002. Takes Nikon lenses. ISO 80-640. 907 g. No mocrolens, IR, or anti-aliasing filter. Noisy sensor; other problems. This image shows the aliasing.  s = 0.48 . IR | RG
Nikon D100
Nikon D70
Pentax *ist D
23.7x15.6
(28.4)
3008x2000
(6.0)
7.8 58.8 / 80.4 0.83 1499
999
1699
Nikon, Pentax use similar sensor. Competitive with the EOS 10D. s = 0.48. IR (D100) | SD (D100) | SD (*ist D)
Olympus E-1 17.4x13.1
(21.8)
2560x1920
(4.92)
6.8 66.8 / 91.4  0.72 1799 4/3 inch Kodak sensor. New "open standard" interchangeable lens system. s = 0.54.
Sigma SD9/ SD10
(Photo.net preview)
20.7x13.8
(24.9)
2268x1512
(3.43)
9.12 64.7 / 83.7 0.80 999 for SD9
kit w/2 lenses
1599 for SD10
kit w/2 lenses
Foveon F7 CMOS sensor with X3 technology: 3 colors per pixel; fewer artifacts than Bayer sensors (no color Moiré). s = 0.50. IR (SD9) | SD (SD9) | SD (SD10)
Compact digital cameras (high-end "prosumer" models)
Minolta Dimage 7i
Nikon Coolpix 5700
Sony DSC-F717
Olympus E-20
8.70x6.53
(~11)
"2/3 inch"
2560x1920
(4.92)
3.4 130/186 0.70*
*Pessimistic;
see note [7].
1000 (7i)
1200 (5700)
1000 (F717)
1500 (E-20)
Sensors have 1/4 the length and 1/16 the area of full-frame 35mm. Tiny pixels have more noise and less exposure range. No anti-aliasing filter. Lens MTF data is unavailable. s = 0.70SD (E-20)
Sony DSC-F828
Nikon Coolpix 8700
8.8x6.6
(11)
"2/3 inch"
3264 x 2448
(8)
2.7  -- See note [7]. 999 The tiny pixels are a source of controversy. Severe purple-fringing at saturated high contrast boundaries. Sony's four-color sensor includes cyan pixels.  LL | IR (F828) | SD (8700)
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Notes
1. Links in the Camera column are to DPreview.com reviews, if available. Other review sites: IR: Imaging-resource.com | SD: Steves-digicams.com | RG: RobGalbraith.com | LL: Luminous-Landscape.com
2. Imaging-resource.com has a nice chart comparing features of high-end digital cameras.
3. MTF is calculated by the MTFCurve2 program, assuming the excellent lens and sharpening. For digital sensors, I entered  mtfcurve2 1e4 0 61 2 dscan sincpwr s,  where  dscan = 1000/pixel spacing in µm (pixels/mm); sincpwr = 3 for Bayer sensors with anti-aliasing, 1.5 for Foveon X3 sensors; s = sharpening, set so MTF at low spatial frequencies is about 0.7 of peak MTF.
3A. Film (Provia 100F scanned at 4000 dpi and sharpened, which results in sharper prints than conventional enlargements) has about the same spatial resolution as anti-aliased Bayer sensors with 10.2 micron pixels.
4. Resolution relative to 35mm is calculated by the equation, (50% MTF)/46.7 * (sensor height)/24. This is linear (not total, or area) resolution.
5.A very nice Japanese page compares D30, D60 and 1D images. They also compare the D100, D1X and D60. Luminous-Landscape.com's D60 review compares D30, D60 and Provia images using the excellent lens. The images support my numbers better than the text.
6. You can get about 20% more resolution form a perfect film image with an 8000 dpi drum scan, but I chose 4000 dpi for the benchmark because few photographers can afford 8000 dpi scans on a regular basis.
7. Lenses for compact digital cameras (11mm or smaller diagonal sensors) should be sharper (have more extended MTF response) than 35mm lenses because they cover a much smaller area and tend to have optimum sharpness at larger apertures, around f/4 - 5.6. But MTF data for these lenses is unavailable, so I based the resolution relative to 35mm on the "excellent 35mm lens." This is pessimistic; the actual number is undoubtedly higher. I won't simulate the Sony DSC-F828 until I have good lens data. Measured results are on Imatest Sharpness comparisons.

Crop of EOS 10D image. Click to see more details.Based on the equivalence of 10.2 micron pixels with film, I estimate that a full-frame sensor with 8.3 megapixels would have resolution equal to 35mm film. Slightly more pixels would be required for smaller sensors with lenses designed to cover full-frame 35mm. The simulated resolution of the Canon EOS 10D relative to 35mm film (82%) agrees well with my tests on the 10D. Likewise, the simulated resolution of the Nikon D100 agrees with Dennis Wilkins' tests.

The image on the right was cropped from a 3072x2048 pixel image taken with the EOS 10D. Details can be found on the EOS 10D page. It illustrates how digital cameras make highly efficient use of pixels; images tend to be sharper at the pixel level than 35mm scans. There are no MTF losses from film, film flatness error, development, or scanning (optical and mechanical). Sharpness is consistent and there is little noise/grain. That's why digital camera images achieve comparable perceived image quality with fewer pixels.

In interpreting these results, remember that resolution is not the only factor that influences image quality. Digital cameras with large pixels (over 5 µm) have far less noise (the equivalent of grain) than film, hence they will have better image quality with the same resolution. I find the image quality in my 6.3 megapixel Canon EOS 10D to be equal to 35mm film-- remarkable when you consider that 35mm film exposed and processed with excellent technique (fine lens around optimum aperture, perfect focus, sturdy tripod) can produce remarkably sharp 13x19 inch prints-- finer than most people realize. I haven't used much film (except for the Hasselblad XPan) since I got it.

Michael Reichmann's article, Ultimate Shoot-out, compares his 11 Megapixel EOS-1Ds to the medium format Pentax 67II. Although I agree with his conclusion that the EOS-1Ds has better overall image quality-- I'd buy one today if I could comfortably afford it-- I have to dispute one important detail: which camera has the higher resoluton. It's the Pentax. You can see it on the enlargements of the windows in the middle of the page, the second set of images under The Print Evaluation. A vertical line on the wall on the right is visible in the Pentax image but not in the EOS-1Ds image. Should this change Michael's essential conculsions? No. This thin line represents response at a very high spatial frequency that would have little effect on the appearance of a 13x19 inch image. It would be visible on a 24x30 inch image, but the 1Ds still has superior image quality due to the absence of grain-- see the discussion on Shannon channel capacity and image quality. Sharpness is only a part of the equation. Reichmann's earlier review of the D60, with side-by-side images from the D30, D60, 35mm and medium format cameras, is also worth reading.

The Foveon X3 sensor is an important step above the traditional Bayer mask sensor; images will look better at the same pixel count because of reduced artifacts (Moiré, etc.). But Foveon needs to increase the pixel count of its sensors to compete successfully.

Digital cameras vs. film, part 2 | Dennis Wilkins' tests | The future of digital cameras | Links
Information theory and image quality | MTF from Dpreview.com test results




Images and text copyright © 2000-2014 by Norman Koren.
Norman Koren lives in Boulder, Colorado, founded Imatest LLC in 2004, previously worked on magnetic recording technology. He has been involved with photography since 1964.