DWT, DCT and SVD Based Hexagonal Image Compression

Inspired by the human visual sys- tem(HVS), hexagonal grid computation bears numerous advantages like equidistance, good angular resolution, isoperimetry and fixed neighbours. As the digital technology is advancing day by day, it is often need to handle large volumes of data for transmission and storage purpose. Hence there is a need to focus on different compression techniques without comprising the data quality for reducing the storage space, faster computation and with less computational cost. Image compression techniques exploits the human visual imperceptibility to encode the image with lesser number of bits for the same image. This paper, presents different compression methods like SVD(Singular Value Decomposition), DCT(Discrete Cosine Transform) and discrete wavelet transform (DWT) for hexagonal image grid. Hexagonal image compression is accomplished by outsourcing hexagonal grid images. The performance comparison for different hexagonal image compression are made against rectangular grid and are analysed from MSE, size of the image, CR and PSNR. Hexagonal grid compression provides better results over all the compression methods when compared to the rectangular grid image compression. Although biological processes inspire the structure, the current state of the art of recording and output devices, are often constrained by their square structure. Therefore resampling techniques are used to outsource hexagonal grid images from the rectangular grid.