Efficient Image Compression Using Laplacian Pyramidal Filters for Edge Images

This project presents a new image compression technique for the coding of retinal and fingerprint images. Retinal images are used to detect diseases like diabetes or hypertension. Fingerprint images are used for the security purpose. In this work, the contourlet transform of the retinal and fingerprint image is taken first. The coefficients of the contourlet transform are quantized using adaptive multistage vector quantization scheme. The number of code vectors in the adaptive vector quantization scheme depends on the dynamic range of the input image.