Comparative Analysis of an Optimal Image Compression Using FDWT at Various Decomposition Level with Different Statistical Numerical Measures for Different Pixel Frame

In this paper, we have also discussed the comparative study of different wavelet-based image compression systems. When wavelet transform is applied to image compression, the chosen wavelet base affects the efficiency of signal strength, pixel values and the quality of the reconstructed image, because the property parameters of different wavelet bases are varied, it is very important to research the correlation between the wavelet base properties and image compression. In this paper, we have discussed various statistical numerical measures and obtained results compared in terms of MSE, PSNR, Normalization and Compression Ratio with lower and higher pixel frames. The main objective of this paper measure the quality of image with statistical numerical measures (PSNR, MSE respectively) using different wavelet families with suitable decomposition level. Different test image with 512 × 512 and 1024 × 1024 pixel frames are used to evaluate the performance of image compression. The final choice of optimal wavelet in image compression application depends on image quality, minimum error, optimum PSNR and computational complexity. The experiments are performed using different wavelets at various levels of decomposition. This results show that Discrete Mayer wavelet with second and fourth level decomposition yields better quality for Lena (1024 × 124) and quality has been degrade as lower pixel frame with fruits( 512 × 512)images. Our results provide a good reference for application developers to choose a good wavelet compression system for their application.