Image Compression Using Column, Row and Full Wavelet Transforms Of Walsh, Cosine, Haar, Kekre, Slant and Sine and Their Comparison with Corresponding Orthogonal Transforms

In this paper, image compression using orthogonal wavelet transforms of Walsh, Cosine, Haar, Kekre, Slant and Sine is studied. Wavelet transform of size N 2 xN 2 is generated using its corresponding orthogonal transform of size NxN. These wavelet transforms are applied on R, G, and B planes of 256x256x3 size colour images separately. In each transformed plane rows/columns are sorted in their descending order of energy, and lowest energy coefficients are eliminated to compress the image. This procedure is repeated for different compression ratios and in each case image is reconstructed. Root Mean Square Error (RMSE) between original image and reconstructed image is calculated to measure the performance of transform. Wavelet transforms are applied in three different ways: Column wavelet, Row wavelet and Full wavelet and their performance is compared using RMSE. From the results it has been observed that, RMSE obtained using full wavelet transform is nearly half than column and row wavelet transform. Also, results of wavelet transforms are compared with results of their orthogonal transforms. Full DCT wavelet transform outperforms all other transforms.