Compression of Images Represented in Hexagonal Lattice Using Wavelet and Gabor Filter

Hexagonal geometry has some advantageous like higher sampling efficiency, consistent connectivity and higher angular resolution. In addition to these advantages, the layout of photo-receptors in the human retina is more closely resembles to the hexagonal structure. It is due to these reasons many researchers have studied the possibility of using a hexagonal structure to represent digital images. Wavelet also have its own advantage and combining wavelet and processing of images in Hexagonal grid, that also will give better performance, because hexagonal wavelet includes the advantages of the hexagonal grid along with the wavelets. In this wok, the wavelet based image compression is performed on both square as well as hexagonal sampled images and the performance is compared using Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). Gabor filter is used for the interpolation of hexagonally sampled images. Compression on hexagonal domain gives better results compared to compression on rectangular domain.