Title :
A perceptually lossless, model-based, texture compression technique
Author :
Campisi, Patrizio ; Hatzinakos, Dimitrios ; Neri, Alessandro
Author_Institution :
Dipt. di Ingegneria Elettronica, Rome Univ., Italy
fDate :
8/1/2000 12:00:00 AM
Abstract :
In natural scenes, still images as well as sequences, backgrounds, and objects´ surfaces usually have a textural structure. Therefore, in order to efficiently code images it is crucial to investigate the texture compression problem. In this paper, a perceptually lossless, synthesis-by-analysis texture coding method is presented. The proposed approach is model based; the parameters of the model consist of a binary excitation signal and the parsimonious representation of the reconstruction filter. The estimated parameters, which allow to one synthesize, at the decoder site, a texture that is perceptually indistinguishable from the original one, are then compressed using a lossless strategy, which is based on a fast binary wavelet transformation specifically tailored to binary images. The proposed method leads to very good perceptual results superior to those of existing techniques
Keywords :
data compression; decoding; filtering theory; image coding; image reconstruction; image sequences; image texture; natural scenes; parameter estimation; transform coding; two-dimensional digital filters; wavelet transforms; 2D filters; backgrounds; binary excitation signal; binary images; decoder site; estimated parameters; fast binary wavelet transformation; image coding; image sequences; model-based texture compression; perceptually lossless texture compression; progressive coding; reconstruction filter representation; still images; synthesis-by-analysis texture coding; textural structure; Entropy; Humans; Image coding; Image storage; Layout; Quantization; Signal synthesis; Surface texture; Visual system; Wavelet transforms;
Journal_Title :
Image Processing, IEEE Transactions on