In this, we performed compression of an image by using Hybrid (DWT & DCT) technique. Standard wavelet filters of Haar, Daubechies, Symlets, Coiflets, BiorSplines & ReverseBior were used to estimate compression performance. Generally any Compression method is trying to reduce number of bits per pixel for sufficient representation of image. So memory needed for storing necessary information is reduced & communication efficiency is upgraded. In modern days, the method of image decomposition with the help of wavelets has attained an immense agreement of reputation. Totally standard wavelet filters are compared with 3 different gray images in the encoding section & tabulated the MSE Vs PSNR simulation results. These results offered that, Daubechies (db9) wavelet family produced better results with this Hybrid image compression scheme.

In this study, we are presenting WWT (Walsh Wavelet Transform) technique to compress an image. In recent times, DWT (Discrete Wavelet Transform) & WT (Walsh Transform) are developed as a prevalent methods for compressing an image. In this, WT (Wavelet Transform) is one such significant transform of image compression. Outcome of this is altered with the wavelet type changes. In this paper, we used MSE & PSNR parameters to estimate the performance of several wavelets in image compression. The wavelet filters used in this process are Daubechies (db-x), Discrete meyer (dmey), Coiflets (coif-x), Biorthogonal (bior -x), Symlets (sym-x), Reverse Biorthogonal (rbiox) along with 3 different color images. With this results,it is suggested that good choice of wavelet improves the quality as well as PSNR remarkably. MSE versus PSNR simulation results are tabulated with different wavelet filters. These results yielded 'dmey' wavelet filter produced better results.