Image analysis – Image compression or coding – Pyramid – hierarchy – or tree structure
Reexamination Certificate
2000-02-04
2003-10-21
Couso, Jose L. (Department: 2721)
Image analysis
Image compression or coding
Pyramid, hierarchy, or tree structure
Reexamination Certificate
active
06636643
ABSTRACT:
FIELD OF INVENTION
This invention related to image processing methods and more particular to a system and method for using stochastic resonance and image replacement to improve the appearance of a compressed image.
SUMMARY OF THE RELATED ART
Various compression approaches are in use today which generate undesirable artifacts. These artifacts are often on fixed boundaries, or consist of patterns uncommon in natural images. For example, Discrete Cosine Transforms of images is a technique widely used to reduce the amount of data in an image file. This consists of transforming parts of the image, typically blocks of 8×8 or 16×16 pixels. This method is limited in efficiency because it does not take full advantage of features which cross block boundaries, and it tends to generate tiled artifacts at block boundaries which are very obvious to viewers.
Compression methods, such as full image wavelet transforms, can be used to avoid some of the traditional classes of artifacts. The resulting images can still have an unnatural appearance due to the lack of noise and due to image elements blurring together unnaturally as a result of the subband or wavelet processing. At extreme compression levels, the quantified data sets do not adequately represent the original continuous image. These result in artifacts described as “flat”, “blurry”, “lumpy”, “speckled”, “ringing”, or “evaporating”.
SUMMARY OF INVENTION
The system and method of the present invention take advantage of a stochastic resonance-type process to improve the information transfer, compensate for the quantification error, and replace any energy removed by the quantification process with the appropriate uncertainty in the output. In this way, complete compensation for any unnatural appearance in the resulting image due to quantification error is achieved. As the compression is increased, the resulting image has the appearance of being seen or photographed under progressively worse lighting conditions. It retains its natural appearance, while the information content and perceived quality degrades in a very natural and acceptable manner, with none of the traditional compression artifacts.
The present invention manipulates the component data classes resulting from subband partitioning of an image or signal to improve the efficiency and characteristics of the resulting signal. The result can most easily be described as producing a “film look” as a result of how quantification uncertainty is manipulated.
In the preferred embodiment of the present invention, a subband transform is performed on an image generating components that represent either high or low and DC frequency components. The data components which contain DC information are linearized by the addition of a function that has a probability and magnitude distribution similar to the quantification error. The linearizing function is a generator of random values chosen so that it is exactly reproducible and provides a reasonably close model of the error distribution. In the final step, the data is then dequantified by the reverse process, which can range from a simple linear multiplication, to complex nonlinear, adaptive, and table lookup processes.
In an alternative embodiment, a method is provided which linearizes large magnitude signals only and can avoid the increased size problem by operating on values which result in quantified magnitudes other than 0. In this embodiment, the linearizing function distribution is chosen as in the preferred embodiment but is now used to modulate the quantification function around zero. Ideally the selected linearizing function distribution will have a minimum range matching the original zero range and a maximum range equal to the original range plus the linearizing function range. This results in an increase in the number of zero values while at the same time linearizing the quantifier for large magnitude values. The result is then dequantified by reproducing the linearizing function and reversing the quantification process. To dequantify zero values, a dither function with a distribution similar to the quantification error may be used as the range resulting from dequantification of zero values is not linearized. In both cases, the subbands are then recombined to create a new image with the enhanced “film look”.
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patent: 6134350 (2000-10-01), Beck
patent: 6141446 (2000-10-01), Boliek et al.
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patent: 6298160 (2001-10-01), Goertzen
Bromberg & Sunstein LLP
Couso Jose L.
Quvis, Inc.
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