No abstract

This paper presents an objective video quality evaluation method for quantifying the subjective quality of digital mobile videos. The proposed method aims to objectify the subjective quality by extracting edge region features and blockiness parameters. To evaluate the proposed algorithm's performance, we carried out subjective video quality tests with the Double-Stimulus Continuous Quality Scale (DSCQS) method and obtained differential mean opinion score (DMOS) values for 140 video clips (CIF/QCIF). We then compared the proposed method's performance to that of existing methods in terms of DMOS estimation accuracy. Experimental results show that the proposed method is approximately 25% better than the EPSNR method in estimating actual DMOS values.

We propose a quality assessment method from decoding parameters of compressed bitstreams by scalable video coding (SVC) as a hybrid/bitstream category. Conventional video quality assessment methods evaluate the video quality of degraded videos after full reconstruction. However, the proposed assessment method quantifies video quality of SVC not only with reconstructed videos for the base layer but also with decoding parameters for the enhancement layer. The proposed algorithm assesses the enhanced quality degree of the enhancement layers with statistics of various coding parameters for the enhancement layers with respect to the quality of the base layer. The accuracy of the proposed algorithm is 23% higher than those of conventional algorithms in terms of Pearson correlation. Furthermore, the proposed algorithm has significantly lower computational complexity than conventional methods.

No abstract

This paper presents an objective video quality evaluation method for quantifying the subjective quality of digital mobile video. The proposed method aims to objectify the subjective quality by extracting edgeness and blockiness parameters. To evaluate the performance of the proposed algorithms, we carried out subjective video quality tests with the double-stimulus continuous quality scale method and obtained differential mean opinion score values for 120 mobile video clips. We then compared the performance of the proposed methods with that of existing methods in terms of the differential mean opinion score with 120 mobile video clips. Experimental results showed that the proposed methods were approximately 10% better than the edge peak signal-to-noise ratio of the J.247 method in terms of the Pearson correlation. C 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).Subject terms: quality of experience; subjective video quality; mean opinion score; double-stimulus continuous quality scale; video quality experts group.Paper 100707RRR