Image Compression using Hybrid Slant Wavelet where Slant is Base Transform and Sinusoidal Transforms are Local Transforms

Many transform based image compression methods have been experimented till now. This paper proposes novel image compression method using hybrid slant transform. Slant transform is used as base transform to focus on global features of an image. Sinusoidal orthogonal transforms like DCT, DST, Hartley and Real-DFT are paired with slant transform to generate hybrid slant wavelet transform. Performance of hybrid slant wavelet can be compared by varying the size of its component transform. Along with RMSE which is commonly used parameter, Mean Absolute Error, AFCPV and SSIM are the parameters used to observe the perceptibility of compressed image. It has been observed that, hybrid slant wavelet generated using 8x8 Slant and 32x32 DCT gives lowest error at compression ratio 32 as compared to other sinusoidal transforms when paired with slant transform. Performance of hybrid slant wavelet is compared with its multi-resolution analysis which includes semi-global features of an image and with hybrid transform that includes global features of image. Comparison shows that, hybrid wavelet has given good image quality than hybrid transform and its multi-resolution analysis.