Encoding and decoding of color digital image using wavelet and fractal encoding
First Claim
1. A method for compressing color digital image data, wherein said color digital image data is separated into a plurality of different color data groups, comprising the steps of:
- transforming one of said groups of color data into a different selected color, wherein said different selected color is more indicative of edges in said image than said data group which is transformed;
spatially decomposing each of said groups of image data into high frequency and low frequency images at a plurality of scales of decreasing frequencies;
fractally encoding said high frequency data for each said group responsive to said high frequency data at said scales generated for said group; and
storing separately encoded data for each said group data responsive to said fractal encoding and comprising information representing modulus and angle relationships between portions of said image at said plurality of scales.
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Abstract
Color digital image data is encoded and compressed by a technique which combines the advantages of both wavelet and fractal encoding. The technique produces an encoded image separated by color components which can be efficiently matched to other compressed images in order to identify the image being processed. The encoding technique divides the images at numerous scales produced by wavelet transformations and forms blocks comprising of groups of pixels at each scales. The average modulus values and average angles values of the data in each of the blocks are compared to the next higher scale. Each scale is then encoded for the blocks which have corresponding matching blocks in the adjacent scale. The technique provides the edge retention benefits of wavelet and the compression benefits of fractal encoding and also accelerates the matching process between the scales. A decoding technique which uses a cross scale approximation of wavelet coefficients is used to reconstruct the image.
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Citations
34 Claims
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1. A method for compressing color digital image data, wherein said color digital image data is separated into a plurality of different color data groups, comprising the steps of:
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transforming one of said groups of color data into a different selected color, wherein said different selected color is more indicative of edges in said image than said data group which is transformed; spatially decomposing each of said groups of image data into high frequency and low frequency images at a plurality of scales of decreasing frequencies; fractally encoding said high frequency data for each said group responsive to said high frequency data at said scales generated for said group; and storing separately encoded data for each said group data responsive to said fractal encoding and comprising information representing modulus and angle relationships between portions of said image at said plurality of scales. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. The method for processing compressed color digital image data representing an original color image, wherein said image data has been spatially decomposed into a plurality of scales, wherein information representing modulus and angle value relationships between portions of said image at the plurality of scales and a representation of said image at the lowest scale has been stored, the method comprising the steps of:
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a. spatially decoding said stored representation; b. decoding said spatially decoded representation responsive to said stored relationship information; c. transforming said decoded representation in step b to a representation in a next scale; and d. repeating steps b and c until said representation closely approximates the original image. - View Dependent Claims (17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28)
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29. A system for processing compressed color digital image data to reconstruct said color digital image comprising:
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a storage medium for storing information indicative of said compressed image which has been spatially decomposed into a plurality of scales, wherein said information comprises information representing modulus and angle value relationships between portions of said image at the plurality of scales; at least one processor which repeatedly transforms said compressed image by fractally decoding and spatially reconstructing said stored information at a plurality of scales using said relationships, wherein said image information is repeatedly transformed until said compressed image approximates the original image; and a display for displaying said reconstructed image. - View Dependent Claims (30, 31, 32, 33, 34)
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Specification