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.

Abstract: 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 which can be efficiently matched to other compressed images in order to identify the image being processed. The encoding technique spatially decimates the images at numerous frequency scales produced by wavelet transformations and forms blocks comprising of groups of pixels at each frequency scales. The average modulus values and average angle values of the data in each of the blocks are compared to the next higher scale. Each frequency 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 fractal encoding and also accelerates the matching process between the scales. A decoding technique which includes a synthetic edge procedure is used to reconstruct the image.

Abstract: 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 which can be efficiently matched to other compressed images in order to identify the image being processed. The encoding technique spatially decimates the images at numerous frequency scales produced by wavelet transformations and forms blocks comprising of groups of pixels at each frequency scales. The average modulus values and average angle values of the data in each of the blocks are compared to the next higher scale. Each frequency 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 fractal encoding and also accelerates the matching process between the scales. A decoding technique which includes a synthetic edge procedure is used to reconstruct the image.