Technical Articles

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Characterization and measurement of color fringing

This article explains the cause of the color fringing phenomenon that can be noticed in photographs, particularly on the edges of backlit objects. The nature of color fringing is optical, and particularly related to the difference of blur spots at different wavelengths. Therefore color fringing can be observed both in digital and silver halide photography. The hypothesis that lateral chromatic aberration is the only cause for color fringing is discarded. The factors that can influence the intensity of color fringing are carefully studied, some of them being specific to digital photography. A protocol to measure color fringing with a very good repeatability is described, as well as a mean to predict color fringing from optical designs.

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Does resolution really increase image quality?

A general trend in the CMOS image sensor market is for increasing resolution (by having a larger number of pixels) while keeping a small form factor by shrinking photosite size. This article discusses the impact of this trend on some of the main attributes of image quality. The first example is image sharpness. A smaller pitch theoretically allows a larger limiting resolution which is derived from the Modulation Transfer Function (MTF). But recent sensor technologies (1.75μm, and soon 1.45μm) with typical aperture f/2.8 are clearly reaching the size of the diffraction blur spot. A second example is the impact on pixel light sensitivity and image sensor noise. For photonic noise, the Signal-to-Noise-Ratio (SNR) is typically a decreasing function of the resolution. To evaluate whether shrinking pixel size could be beneficial to the image quality, the tradeoff between spatial resolution and light sensitivity is examined by comparing the image information capacity of sensors with varying pixel size. A theoretical analysis that takes into consideration measured and predictive models of pixel performance degradation and improvement associated with CMOS imager technology scaling, is presented. This analysis is completed by a benchmarking of recent commercial sensors with different pixel technologies.

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Sensor spectral sensitivities, noise measurements and color sensitivity

This article proposes new measurements for evaluating the image quality of a camera, particularly on the reproduction of colors. The concept of gamut is usually a topic of interest, but it is much more adapted to output devices than to capture devices (sensors). Moreover, it does not take other important characteristics of the camera into account, such as noise. On the contrary, color sensitivity is a global measurement relating the raw noise with the spectral sensitivities of the sensor. It provides an easy ranking of cameras. To have an in depth analysis of noise vs. color rendering, a concept of Gamut SNR is introduced, describing the set of colors achievable for a given SNR (Signal to Noise Ratio). This representation provides a convenient visualization of what part of the gamut is most affected by noise and can be useful for camera tuning as well.

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Advances in Camera Phone Picture Quality

A unique digital postprocessing technique compensates for performance problems posed by ever-shrinking pixels

by Dr. Guichard Frédéric, DxO Labs
From Photonics Spectra, November 2007

As camera phones become ubiquitous, consumer demand for a photographic experience similar to that of traditional digital cameras is growing. Coupled with the ready availability of high-definition displays, this need has translated into a requirement for higher-resolution cameras in mobile phones. However, handset design aesthetics impose a much smaller form factor for the miniature camera modules built into hand-sets than can be accommodated by reusing the same technology found in digital still cameras.

One of the most challenging aspects of designing a high-resolution camera for a mobile phone is the limitation on the overall height of the camera, measured from the top of the lens to the back of the camera substrate. The typical target height is 6 mm or less, unless a more expensive folded-optics design is considered. Given the angular acceptance of CMOS image sensor pixels, the maximum-size sensor that can be used with such a thin camera measures approximately 4.5 mm diagonal. To increase the resolution without increasing the height of the camera (or thickness of the phone), more pixels must fit into the array defined by this diagonal size. Using a 2.2-× 2.2-µm-pixel size, 2-megapixel sensors can be used in these thin cameras. To achieve 3.2-megapixel resolution, 1.75 × 1.75-µm-pixel size must be used, and 5-megapixel resolution requires 1.4 × 1.4-µm pixel.

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