Abstract— this research presents a new algorithm for an image compression consist of three phases; the first phase is using "Discrete Wavelet Transformation (DWT)", to produce low-frequency and high-frequencies sub-bands. The high-frequencies sub-bands are ignored (i.e. not used in this research), in the second phase used "Discrete Cosine Transformation (DCT)" applied on each "2x2" block from "LL" sub-band, then each block stored as a onedimensional array in the new matrix called "Multi-Array- Matrix (MA-Matrix)". The third phase; MA-Matrix separated into "DC-Column" and "MA2-Matrix", and then applied Minimize-Matrix-Size algorithm on the "MA2- Matrix", to be as a one-dimensional array. Our decompression algorithm phase starts from "Sequential Search Algorithm (SS-Algorithm)" to find the estimated values for the "MA2-Matrix". The SS-Algorithm depends on the three pointers, for decompress MA2-Matrix, and then combined it with DC-Column for reconstructs MA-Matrix. Finally the inverse DCT and the inverse DWT are used for reconstructs approximately original image. Our approach compared with JPEG and JPEG2000 by using PSNR.

Index Terms— Discrete Wavelet Transform, Discrete Cosine Transform, Minimize-Matrix-Size Algorithm, Sequential Search Algorithm.

Cite: Mohammed Mustafa Siddeq, "Using Sequential Search Algorithm with Single level Discrete Wavelet Transform for Image Compression (SSA-W)," Journal of Advances in Information Technology, Vol. 3, No. 4, pp. 236-249, November, 2012.doi:10.4304/jait.3.4.236-249