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Research Article | Open Access
Volume 11 | Issue 1 | Year 2024 | Article Id. IJEEE-V11I1P101 | DOI : https://doi.org/10.14445/23488379/IJEEE-V11I1P101

Mapping of Temporal Space Slicing for Video Quality Metrics Assessment

Shilpa Bagade, Budati Anil Kumar, L. Koteswara Rao

Citation :

Shilpa Bagade, Budati Anil Kumar, L. Koteswara Rao, "Mapping of Temporal Space Slicing for Video Quality Metrics Assessment," International Journal of Electrical and Electronics Engineering, vol. 11, no. 1, pp. 1-7, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I1P101

Abstract

Full-Reference (FR) video quality evaluation approach that combines frame-based Visual Quality Assessment (VQA) with analysis of space-time slices to provide an efficient video quality predictor is proposed. The sample and test video clips are first put into a temporal space slice form by the proposed method. Each reference-test video pair is subjected to the computation of several distortion-aware maps to define space-time distortions more thoroughly. Then, a standard visual quality model, such as Peak Signal to Noise Ratio (PSNR) or Structural Similarity Index (SSIM), is used to process these reference-distorted maps. A final video quality score is created by combining several VQA outputs using a straightforward, learnt pooling method. The method thoroughly evaluated the Temporal Space Slicing (TSS) algorithm using three publicly accessible video quality assessments and discovered that TSS-PSNR performed noticeably better than leading-edge video quality models.

Keywords

HEVC, Packet loss, Video streaming, Video compression, Video Quality Metrics.

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