Image Scaling Comparison Using Universal Image Quality Index

Image interpolation has many applications in computer vision, image processing and biomedical applications. Resampling is required for discrete image manipulations, such as geometric alignment and registration, to improve image quality on display devices or in the field of lossy image compression wherein some pixels are discarded during the encoding process and must be regenerated from the remaining information for decoding. The comparison is done for different interpolation techniques such as nearest neighbor, bilinear and bicubic interpolation and the comparison is done for different interpolation schemes using universal image quality index. In this paper an attempt is made to highlight the universal quality index by comparing with error measures such as MSE and PSNR.