The full text of this article/chapter:

Improving the Performance of Adaptive Linear Prediction Coding (ALPC) Via Least Square Minimization
by Giovanni Motta, James A. Storer, Bruno Carpentieri
12th International Workshop on Systems, Signals and Image Processing (IWSSIP), Vol. 1, No. 1, 2005
Abstract: Recently proposed state of the art lossless image compressors could be divided in two categories: single and double pass compressors. While in the first category, that includes CALIC and JPEG-LS, linear prediction is very little used; TMW, a state of the art double pass image compressor relies on linear prediction for its performance. ALPC is a single pass adaptive algorithm that uses context classification and multiple linear predictors, locally optimized on a pixel-by-pixel basis. On the average, ALPC obtains a compression ratio comparable to CALIC while improving on some images. In this paper we review the ALPC coder and improve its performance by using an approach based on least square minimization. The resulting algorithm is faster than the original ALPC and improves on its compression.

is only available to individual subscribers or to users at subscribing institutions.

Pay per view: If you are not a Subscriber and you just want to read the full contents of this article, please click here to purchase online access to the full-text of this article. Please allow 3 days + mailing time. Current price for article is US$38.00

Members of the Editorial Board or subscribers of the 12th International Workshop on Systems, Signals and Image Processing (IWSSIP), that have been redirected here, please click here if you have IP-authentication access, or check if you have a registered username/password subscription with Inderscience. If that is the case, please Login:

    Username:        Password:         Forgotten your Password?