As the requirement for Image Quality Evaluation is needed in many application areas. Image quality review is one of the challenging fields of digital image processing system. Measurement of visual quality is of fundamental importance for abundant image and video processing applications, where the goal of quality assessment (QA) algorithms is to automatically assess the quality of images or videos in agreement with human quality judgments. The evaluation of image quality based on single strategy Human Vision System (HVS) may not very sufficient. We need some more dimensions. Full Reference method. Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Average Difference (AD), Normalized Absolute Error (NAE), Structural Content (SC) and Maximum Difference (MD) may contribute to calculate efficient result to image quality measurements.
Cite this article:
Deepak Kumar Dewangan, Yogesh Rathore. Image Quality Costing of Compressed Image Using Full Reference Method. Int. J. Tech. 1(2): July-Dec. 2011; Page 68-71
Deepak Kumar Dewangan, Yogesh Rathore. Image Quality Costing of Compressed Image Using Full Reference Method. Int. J. Tech. 1(2): July-Dec. 2011; Page 68-71 Available on: https://www.ijtonline.com/AbstractView.aspx?PID=2011-1-2-4