Implementing image compression using transform based approach

Nowadays there is an increased need to store images in all the fields such as medicine, engineering, industries. Mostly techniques like wavelet and discrete cosine transform have been implemented. Several techniques have been developed for lossy and lossless image compression, several techniques were developed. Image edges have limitations in capturing them if we make use 1-D wavelet transform simultaneously in 2 dimensions. This is because wavelet transform cannot effectively represent straight line discontinuities and be reconstructed in a proper manner like that of curvelet transform. The Curvelet Transform is more suitable for compressing images, which has more curved portions. Fast discrete curvelet transform is implemented is used that is implemented using stationary wavelet transform. The proposed method is tested on various medical images and the result shows better performance parameters like Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR) and Mean Square Error.