Reduced reference blockiness and blurriness meter for image quality assessment

Abstract

This research work demonstrates an image quality assessment meter (IQAM) in reduced reference (RR) mode for discrete cosine transform (DCT) based compressed images. The DCT based image compression technique is lossy. As a result, it introduces blockiness and blurriness artefacts in the coded image. To send the image in image transmission systems, the system bandwidth is limited, and image data need to be adapted accordingly. To determine the quality of image at the recipient end, fewer image parameters are sent rather than the complete reference image. The aim of this paper is to suggest a method for the receiver to evaluate the objective received image quality. The presented RR quality meter operates in the frequency domain for the estimation of artefacts in the compressed image. The quality meter takes the image, performs edge detection, transforms it into the frequency domain and estimates the harmonics. The estimated strength of harmonics in the compressed image is compared with the received RR parameter for blockiness and blurriness distortions. For improved quality judgment, the combined effect of both these artefacts is measured as well. Peak signal to noise ratio (PSNR) is another most familiar method of image quality assessment. The received image quality is also observed by measuring the PSNR. The objective values of the artefacts obtained by the designed RR IQAM algorithm are correlated with the subjective differential mean opinion scores (DMOS) blockiness and blurriness values of Laboratory for Image and Video Engineering (LIVE) image database2. The results obtained are well matched and give 93–94% correlation with the LIVE database values, whereas the correlation obtained by PSNR values with LIVE DMOS values is only around 70%. This proves the practical application of the designed IQAM in RR.

Keywords:

• Image processing
• Blockiness
• Blurriness
• Reduce reference
• Image quality assessment
• PSNR