Abstract

Image transforms are widely used in Image processing and Image analysis. Image transforms are useful for fast computation of convolution and correlation. Image Scaling refers to the resizing of images in digital image processing. The resolution of images is a major factor when the images are enlarged. The enlarging of images in turn refers to the up sampling, when the image is up sampled, there will be a decrease in the image quality. To improve the quality of the image, different interpolation techniques has been proposed. The main objective of this paper is to study different interpolation techniques for scaling of images such as nearest neighbor, bilinear interpolation and bicubic interpolation and compared in both frequency domain and spatial domain.

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