Total views : 172

Resolution Analysis of Grey Scale Image using Spherical Harmonics (SPH) Method

Affiliations

  • School of Electronic and Information Engineering, Changchun University of Science and Technology, Changchun - 130022, China

Abstract


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.

Keywords

Euclidean Distance (ED), Grey Scale Image, Mean Square Error (MSE), Peak Signal To Noise Ratio (PSNR), Spherical Harmonics (SH), Spherical Texture Mapping, Unit Sphere.

Full Text:

 |  (PDF views: 165)

References


  • Frederick MW, Venkat D. Texture mapping 3D model’s of real–world Scenes. ACM Computing Surveys. 1997 Dec; 29(4):325-65.
  • Pooja K, Yuvraj S. Comparison of different image enhancement techniques based upon PSNR and MSE. International Journal of applied Engineering and Research. 2002; 7(2):1-11.
  • Kaiwen Z, Shuozhong W, Xinpen Z. A new metric for quality assessment of digital images based on weighted-mean square error. Proceedings of SPIE; 2002 Jul. p. 1-6.
  • Jing L, Bao LL. An adaptive image Euclidean distance. Elsevier. 2008 Jul; 42:349-57.
  • Wojceich J, Natan AC, Henrick WJ. Importance sampling spherical harmonics. Computer Graphics Forum. 2009 Apr; 28(2):577-86.
  • Bennet MA, Nair RR, Mahalakshmi V, Janakiraman V. Performance and analysis of ground-glass pattern detection in lung disease based on high-resolution computed tomography. Indian Journal of Science and Technology. 2016 Jan; 9(2):1-7.
  • Sakthivel M, Dhayalan D, Babu MS, Murugan JS. Robust aircraft recognition using high resolution reconstructed images. Indian Journal of Science and Technology. 2016 Jan; 9(3):1-7.
  • Ashima, Mohana R. Anaphora resolution in Hindi: Issues and directions. Indian Journal of Science and Technology. 2016 Aug; 9(32):1-8.
  • Jung YH, Park K, Chae JM, Jung SY. Resolution of ellipse in coordinate noun phrases. Indian Journal of Science and Technology. 2015; 8(21):1-5.

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.