ICRS: inter-layer compression method combined with generation of a spatial image pyramid

Abstract

Currently, generating spatial image pyramid data mainly relies on down-sampling filtration, but so far, there is not any way to evaluate the effect of down-sampling. Herein, down-sampling and up-sampling were combined to form a pair of re-sampling filter, called RSFP, serving as an approximation of the current layer of pyramid data, can be used to evaluate the effect of the down-sampling filter. Based on RSFP, a pyramid-generating approach was built up in here, called it as TDFA. Its filtering depends on the texture direction of the pyramid image data. TDFA down-sampling PSNR was higher than the nearest neighbor interpolation, about 4.51---5.70 dB, while the latter was ever known the best down-sampling filter. The traditional JPEG compression method ignored the close correlations among the pyramid interlayer data, its compression process does not depend on the image texture features, which is not conducive to improving the compression ratio. The proposed RSFP and texture filtering method TDFA can effectively remove both correlations of pyramid image data, which respectively are the inter-layer correlations and its intra-layer texture correlations. Based on the re-sampling filter pair RSFP, combing these two means, an inter-layer compress method ICRS was created in this paper. Under the same reconstruction conditions, ICRS was found to increase the compression ratio 6.02 to 19.70 higher than the conventional AVS's I-frame algorithm, and on the whole, its compression ratio is 3 times or more high than that of JPEG algorithm, and there still is considerable room for improvement.