WAVELET BASED METHOD FOR REMOVING GAUSSIAN NOISE USING BY REPRESENTING IMAGES IN HEXAGONAL LATTICE

Human Visual System (HVS) is for acquiring, processing, analyzing, and understanding the images and this is a natural process. The image acquisition, processing, analysing and understanding the images are electronically duplicated in Computer vision. At present the hardware available for acquiring, processing and displaying is based on square pixel. But, retina of the human eye closely resembles a hexagonal grid space. So if we could able to represent the image in hexagonal domain, the computer vision will be as close to human vision. Keeping this in mind, we proposed a wavelet based image de-noising on hexagonally re-sampled images. In addition to the biological inspiration the hexagonal representation has many other advantages. By considering these advantages of hexagonal representation, in this work we proposed a wavelet based image denoising scheme in hexagonal grid space. For analysing and comparing result obtained in hexagonal grid with square grid image, Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) is used.