This paper presents an improvement of the Visual Pattern image coding (VPIC) scheme presented by Chen and Bovik in [2] and [3]. The patterns in this improved scheme are defined by morphological operations and classified by absolute error minimization. The improved scheme identifies more uniform blocks and reduces the noise effect. Therefore, it improves the compression ratio and image quality i...

The vast amount of data needed to represent digital imagery motivates the use of advanced compression systems to reduce the bandwidth required to transmit high-resolution source imagery. We propose two methods to provide optimal image quality at a fixed image delivery rate. The first method, channel-controlled variable-rate (CCVR) image coding, operates within the constraint that the modulation...

Neural networks have the potential to extend data compression algorithms beyond the character level n-gram models now in use, but have usually been avoided because they are too slow to be practical. We introduce a model that produces better compression than popular Limpel-Ziv compressors (zip, gzip, compress), and is competitive in time, space, and compression ratio with PPM and BurrowsWheeler ...

The performance, emission and combustion characteristics of a single cylinder four stroke variable compression ratio multi fuel engine when fueled with different blends of rice bran oil methyl ester and ethanol are investigated and compared with the results of standard diesel. Bio diesel produced from Rice bran oil by transesterification process has been used in this study. Experiment has been ...

This article presents a new digital image compression scheme which exploits a human visual system property—namely, recognizing images by their regions—to achieve high compression ratios. It also assigns a variable bit count to each image region that is proportional to the amount of information it conveys to the viewer. The new scheme copes with image nonstationarity by adaptively segmenting the...