Title :
A perceptually motivated three-component image model-part II: applications to image compression
Author :
Ran, Xiaonong ; Farvardin, Nariman
Author_Institution :
Dept. of Syst. Technol., Nat. Semicond. Corp., Santa Clara, CA, USA
fDate :
4/1/1995 12:00:00 AM
Abstract :
For past I see ibid., vol.4, no.4, p.405 (1995). The use of the image model of Part I is investigated in the context of image compression. The model decomposes the image into a primary component that contains the strong edge information, a smooth component that represents the background slow-intensity variations, and a texture component that contains the textures. The primary component, which is known to be perceptually important, is encoded separately by encoding the intensity and geometric information of the strong edge brim contours. Two alternatives for coding the smooth and texture components are studied: entropy-coded adaptive DCT and entropy-coded subband coding. It is shown via simulations that the proposed schemes, which can be thought of as a hybrid of waveform coding and feature-based coding techniques, result in both subjective and objective performance improvements over several other image coding schemes and, in particular, over the JPEG continuous-tone image compression standard. These improvements are especially noticeable at low bit rates. Furthermore, it is shown that a perceptual tuning based on the contrast-sensitivity of the human visual system can be used in the DCT-based scheme, which in conjunction with the three-component model, leads to additional subjective performance improvements
Keywords :
adaptive signal processing; data compression; discrete cosine transforms; entropy codes; image coding; image texture; visual perception; JPEG; background; contrast sensitivity; entropy-coded adaptive DCT; entropy-coded subband coding; feature-based coding; geometric information; human visual system; image coding; image compression; image texture; intensity information; low bit rates; objective performance; perceptually motivated model; primary component; smooth component; strong edge information; subjective performance; texture component; three-component image model; waveform coding; Bit rate; Context modeling; Discrete cosine transforms; Humans; Image coding; Image storage; Radio access networks; Transform coding; Vector quantization; Visual system;
Journal_Title :
Image Processing, IEEE Transactions on