Quality Measure of Multicamera Image for Geometric Distortion
Mahesh G. Chinchole, Prof. Sanjeev.N.Jain · International Journal of Engineering Trends and Technology · 2015
To create the multiple events into the single image is a simple way to look all the events in a single look. For this multi- camera images have to combine into single image also known as multi-view image. When we combine the multiple images into single image, due to misalignment and different camera orientation as well as arrangement the geometric distortions comes into picture. The proportional distortion variation between two separate camera images is the main aspect while measuring the required quality of the final image. So the quality measure or quality analysis is the most important (step) or factor in multicamera images. There are several objective & subjective methods have been proposed for single camera images but no such comparable efforts has been taken on multicamera image quality measure. This paper details the methods and results of implementing MIQA multicamera image quality analysis. Here we show the methods like PSNR, MSSIM, and VIF for the measurement of quality of multicamera image and then compare their results with MIQM. The experimental analysis shows the effectiveness of the every method in comparison with others. Here we consider the 1 value for original or reference image and 0 values for complete distorted image. The range of MIQM is ranging from 1 to 0