Image compression based on frequency domain reduction size.

This work proposes a new image compression method based on a DCT (Discrete Cosine Transformed) combined with the Matrix Size Reduction algorithm. The compression algorithm starts by dividing the image into 8x8 blocks, then DCT is applied to each block independently, followed by uniform quantization. After that, a zigzag scan is applied to each block to be a one-dimensional array. Additionally, the array size is reduced by eliminating insignificant coefficients using the Matrix size-reduced algorithm. Afterward, the residual coefficients are compressed by Arithmetic Coding. The Matrix Reduction size algorithm is accomplished based on two different random keys. And then, two adjacent frequency domain coefficients are reduced to a single value. The decompression uses a searching method called Sequential Search Algorithm to decode the previously compressed data to retrieve residual coefficients. These residuals are padded with zeros to rebuild the original 8x8 blocks. Finally, inverse DCT is applied to reconstruct approximately the original image. The experimental results showed that our proposed image compression and decompression have achieved up to 98% compression ratio, keeping most of the visual image quality. [ABSTRACT FROM AUTHOR]