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Resolution Analysis of Grey Scale Image using Spherical Harmonics (SPH) Method
Objectives/Aim: To used spherical harmonics coefficients and spherical texture mapping techniques to increases or decreases the reconstructed image resolution from unit sphere. Methods: We used mat lab as a simulation tool to mapped the grey scale image which is a strings of zeros and ones and also called monochrome or black in white image to mapped a grey scale image to a unit sphere by spherical texture mapping. The spherical Texture mapping used a Spherical co-ordinate system for mapping of grey scale image to extract picture information to unit sphere, we also used mat lab for reconstruction of an image from unit sphere using spherical harmonics coefficients. Findings: We analyzed that by increasing the spherical harmonics coefficients the PSNR value increases and the MSE value decreases because more number of pixels of grey scale image mapped to unit sphere and the image resolution of grey scale improved, while decreasing the value of Spherical harmonics coefficient the PSNR value decreases and MSE value increases, so less numbers of pixels are mapped to unit sphere and the grey scale image resolution decreases. In past it can be used for computer graphics, magnetic field of star and planetary bodies, geoids and for gravitational fields. In this paper we used it for resolution analysis of grey scale image from a unit sphere. Application/Improvements: In future it can also be used for medical images to increase or decrease his resolution, and for color images which consist of three elementary colors red, green, and blue.
Euclidean Distance (ED), Grey Scale Image, Mean Square Error (MSE), Peak Signal To Noise Ratio (PSNR), Spherical Harmonics (SH), Spherical Texture Mapping, Unit Sphere.
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