A Comparative Study of Image Scaling Algorithms
Kranti Kumar Jain1, Tripti Sharma2
1Kranti Kumar Jain, Computer Science & Engineering, Chhattishgarh Swami Vivekanand Technical University/ Chhattrapati Shivaji Institute of Technology, Durg, India.
2Ms. Tripti Sharma, Computer Science & Engineering, Chhattishgarh Swami Vivekanand Technical University/Chhatrapati Shivaji Institute of Technology, Durg, India.
Manuscript received on January 15, 2012. | Revised Manuscript received on February 05, 2012. | Manuscript published on August 30, 2012. | PP: 191-193 | Volume-1 Issue-3, February 2012 | Retrieval Number: C0219021312/2011©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, we propose comparative study of image scale retrieval scheme. To the best of our knowledge, there is less comprehensive study on large-scale evaluation. Our empirical results show that our proposed solution is able to scale for hundreds of thousands of images, which is promising for building scale systems. A comparison of various techniques for Image scaling one digital image in to another is made. We will compare various image scaling techniques such as Gaussian scale mixtures in the wavelet domain, Local Wiener estimate, Multi-scale image scaling, Bayes least squares estimator, Thin Plate Spline based image scaling based on different attributes such as Computational Time, Visual Quality of image scaling obtained and Complexity involved in selection of features.
Keywords: Bayes least squares (BLS), Gaussian scale mixture (GSM), Local Wiener estimate, Multi-scale image scaling, Thin Plate Spline.