Image analysis – Image enhancement or restoration
Reexamination Certificate
2000-04-18
2004-08-03
Mehta, Bhavesh M. (Department: 2625)
Image analysis
Image enhancement or restoration
C348S606000
Reexamination Certificate
active
06771833
ABSTRACT:
TECHNICAL FIELD OF THE INVENTION
The present invention relates to image processing and more specifically to the enhancement of digital images.
BACKGROUND OF THE INVENTION
Digital images, such as scanned photographic images, medical images, satellite images, etc. often contain undesirable noise components. For example, photographic film, such as silver-halide film, contains grains held on a substrate, such as silver-halide, as part of its physical makeup. The characteristics of these grains are a function of the type and format of the film, with faster-speed and smaller-format film typically exhibiting more graininess. It will be understood by those skilled in the art, that silver-halide film refers to photographic film that has used silver halide as the light-sensitive agent. In most existing silver-halide films, the developed silver is turned through coupling agents into a dye image, and the silver is washed out of the film. However, after the wash such films are still commonly called silver-halide films, because their action is based on silver halide.
Color film generally comprises a blue layer, a green layer, a red layer, an antihalation layer, and a transparent substrate. In developed color film, each of the blue, green, and red layers contain dyes that are used to represent blue, green, and red colors in the development process. These dyes couple to developed areas of the film that correspond to developed silver grains. For each layer, the more silver grains that develop in any given area of the image, the greater will be the resulting density of dye in that area.
Grain sizes tend to vary randomly: certain grains are small, certain grains are large, and still other grains have sizes that are in between. During the development process, the grains that were exposed to the most light are the first to develop, and other grains develop as the development process continues. Those areas in which the most grains develop for a given layer will have the greatest density of dye. Each layer of the film has its own random and unique pattern of grain makeup, so that none of the patterns of the different layers are substantially alike. A positive film or a print of an image will also have a grain pattern.
Because graininess may have a deleterious impact on the quality of a photographic image, it is conventional practice in photography to avoid graininess in photographic images as much as possible, for example by using films with slower speeds and larger formats. Unfortunately, many situations exist where it is not possible to use these kinds of film. Also, millions of films with a high degree of graininess have already been processed over the last century. Furthermore, as film ages it tends to decay physically, which can cause distortions that affect its graininess and distort color.
Digital images may be created by scanning negatives, transparencies, or printed photographic images. The quality of such a digital image depends in part on the characteristics of the film image. For example, a digital image captured from a film image will often contain traces of the grains in the film, which comprise most of the “noise” or non-image deviations from image in the digital image. Digital images also often reflect any distortions present in the film itself. The higher the resolution of the scanning, the more grain traces and distortions will be captured in the digital image.
Many scanners modify colors and densities using gamma corrections that affect the perception of graininess. For example, a digital image produced by a scanner attempting to increase shadow contrast to overcome image underexposure will produce an image with amplified shadow grain traces relative to highlight grain traces. For example, in the case of an image of a tree against the sky, the digital image may have areas of dark shadows that have more grain traces than areas of the bright sky. Similarly, the digital image may contain areas of low-detail sky with large numbers of grain traces and areas of high-detail leaves with low numbers of traces. In other words, the range of values for grain traces in these digital images tends to fluctuate widely across intensity. In addition, a scanner may blur, i.e. subdue the high frequency content, image detail or attempt to overcome this blurring by sharpening, i.e. boosting the high frequency content, image detail. In both cases the grain traces are affected in relation to frequency, along with the image. This kind of digital image can be called “un-normalized” with respect to grain traces, and it is also often visually displeasing. This is because the human eye tends to focus on the areas in an image that have the highest amount of grain traces and to visually associate those same amounts to areas that actually have fewer grain traces.
Although one can attempt to improve the quality of a scanned image, such improvements can often only be obtained through labor-intensive alterations, which require a person of relatively high skill to subjectively determine what characteristics should be altered to improve the quality of the final image. As a result, because each image may be individually operated upon, the improvement process is time consuming and improvement of a large number of images may be impractical. Accordingly, another method of enhancing digital images is needed that can enhance a digital image automatically.
SUMMARY OF THE INVENTION
One aspect of the invention is a method of enhancing a digital image comprising at least one image channel. At least one spatial domain segment of a plurality of spatial domain segments of an image channel is transformed from the spatial domain to the frequency domain to create at least one segment transform. The spatial domain segment comprises one of a plurality of spatial domain segments of at least one image channel. At least one noise correction function is generated in response to the segment transform. The noise correction function may then be applied to produce at least one corrected transform wherein the corrected transform depends upon, directly or indirectly, the segment transform. The corrected transform may be transformed from the frequency domain to the spatial domain to create at least one corrected spatial domain segment.
The invention has several important technical advantages. Various embodiments of the invention may have none, one, some, or all of these advantages as well as additional advantages. The invention can be used to automatically enhance a digital image with respect to grain traces (noise). Such enhancement may be desirable for use with scanned photographic images. The invention allows automatic calculation of correction arrays for the digital image to correct uneven grain trace distribution with respect to intensity and frequency. Such arrays may be useful to normalize the grain traces in relation to pixel intensities and/or frequency. Once grain traces have been normalized, the invention allows reduction of the grain to a level chosen by a user of the invention, if desired. In addition the normalized grain trace data may be used to balance the digital image's color channels.
Because the invention allows grain normalization and/or reduction to be performed automatically, it can be achieved more quickly, at less cost, and with less knowledge by the person seeking to achieve the normalization and/or reduction than is possible with existing applications.
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XP-000896196: Mei Yu, et al., “New Adapti
Azarian Seyed
Dinsmore & Shohl
Eastman Kodak Company
Mehta Bhavesh M.
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