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M. M. Siddeq, “Image Restoration Using Perception Neural Network,” Master Thesis, Computer Science Department, University of Technology, Iraq, 2001.

has been cited by the following article:

• TITLE: Using Two Levels DWT with Limited Sequential Search Algorithm for Image Compression

  AUTHORS: Mohammed Mustafa Siddeq

  KEYWORDS: DWT; DCT; Minimize-Matrix-Size-Algorithm; LSS-Algorithm; Eliminate Zeros and Store Data

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.3 No.1, February 28, 2012

  ABSTRACT: In this paper introduce new idea for image compression based on the two levels DWT. The low-frequency sub-band is minimized by using DCT with the Minimize-Matrix-Size-Algorithm, which is converting the AC-coefficients into array contains stream of real values, and then store the DC-coefficients are stored in a column called DC-Column. DC-Column is transformed by one-dimensional DCT to be converted into T-Matrix, then T-Matrix compressed by RLE and arithmetic coding. While the high frequency sub-bands are compressed by the technique; Eliminate Zeros and Store Data (EZSD). This technique eliminates each 8 × 8 sub-matrix contains zeros from the high frequencies sub-bands, in another hands store nonzero data in an array. The results of our compression algorithm compared with JPEG2000 by using four different gray level images.