Title: Adaptive multi-level 2D Karhunen-Loeve-based transform for still images

Authors: Roumen K. Kountchev; Kazumi Nakamatsu

Addresses: Department of Radio Communications and Video Technologies, Technical University of Sofia, Bul. Kl. Ohridsky 8, Sofia 1000, Bulgaria ' School of Human Science and Environment, University of Hyogo, Himeji 670-0092, Japan

Abstract: In this work is presented one new approach for block processing of halftone images, based on the adaptive multilevel Karhunen-Loeve (KL) transform. For this, the rows and the columns of the digital image blocks are processed sequentially, using KL matrices of size 2 × 2. As a result, each row of the processed block obtained one vector. The vector components are rearranged in correspondence to their mutual correlation, starting from the highest. After that, on all vectors is applied the next transform level, etc. When the transform for the rows is finished, the processing is executed in a similar way for the columns. The result obtained strong spatial decorrelation of the image blocks elements. The basic advantages of the new algorithm to the famous 2D KL transform are the lower computational complexity and the simplified structure, which offer better opportunities for parallel and recursive image processing.

Keywords: block processing; 2D Karhunen-Loeve transform; adaptive multilevel KL transform; recursive algorithms; image processing; halftone images; computational complexity; spatial decorrelation.

DOI: 10.1504/IJRIS.2014.063953

International Journal of Reasoning-based Intelligent Systems, 2014 Vol.6 No.1/2, pp.49 - 58

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 27 Jul 2014 *

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