Saliency enabled compression in JPEG framework. Issue 7 (1st July 2018)

• Record Type: Journal Article
• Authors: Rahul, Kumar; Tiwari, Anil Kumar
• Is Part Of: IET image processing. Volume 12:Issue 7(2018)
• Page Start: 1142
• Page End: 1149
• Publication Date: 2018-07-01
• Subjects: image coding -- data compression -- image segmentation -- discrete cosine transforms; saliency enabled compression -- JPEG framework -- low bit‐rate requirements -- perceptual quality -- compression artefacts -- region of interest -- ROI dependent quantisation method -- small computational overhead -- discrete cosine transform -- image nonsalient regions -- image salient regions -- goodness‐of‐segmentation -- two‐dimensional DCT coefficients -- 2D‐DCT coefficients -- block rank information -- delta encoding -- objective quality parameters -- visual perception; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2017.0554
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : Under low bit‐rate requirements, JPEG baseline causes compression artifacts in the image. Through this paper, a novel region‐of‐interest (ROI) dependent quantization method in JPEG framework is proposed. The proposed method judiciously quantizes DCT coefficients belonging to salient and non‐salient regions of the image. In this work, multiple ROIs are optimally identified and ranked by using variances. The number of classes is adaptively calculated using goodness‐of‐segmentation. After the number of classes and their ranks are obtained, the image is divided into blocks of size 8 × 8 . These blocks may belong to more than one class and hence these are ranked based on their membership in various classes. 2D‐DCT coefficients of each block are obtained and then quantized adaptively based on their ranks. Overhead for rank information of blocks is minimized by applying delta‐encoding. Results are analyzed in terms of objective quality parameters and visual perception and found that the blocking artifacts in the proposed method are significantly lower than JPEG. The efficiency of the proposed method is demonstrated by results of recently published similar methods and the former is found superior in terms of quality of the reconstructed image.