Low complexity perceptual image coding by just-noticeable difference model based adaptive downsampling

2016 ◽  
Author(s):  
Zhe Wang ◽  
Yousef Baroud ◽  
Seyyed Mahdi Najmabadi ◽  
Sven Simon
Keyword(s):  
Image Coding ◽  
Low Complexity ◽  
Just Noticeable Difference ◽  
Difference Model ◽  
Model Based

scholarly journals A JND-Based Pixel-Domain Algorithm and Hardware Architecture for Perceptual Image Coding

2019 ◽  
Vol 5 (5) ◽  
pp. 50 ◽  
Author(s):  
Zhe Wang ◽  
Trung-Hieu Tran ◽  
Ponnanna Kelettira Muthappa ◽  
Sven Simon
Keyword(s):  
Image Coding ◽  
Predictive Coding ◽  
Rate Distortion ◽  
Visual Quality ◽  
Low Complexity ◽  
Input Image ◽  
Hardware Architecture ◽  
Just Noticeable Difference ◽  
Jpeg 2000 ◽  
Hardware Resource

This paper presents a hardware efficient pixel-domain just-noticeable difference (JND) model and its hardware architecture implemented on an FPGA. This JND model architecture is further proposed to be part of a low complexity pixel-domain perceptual image coding architecture, which is based on downsampling and predictive coding. The downsampling is performed adaptively on the input image based on regions-of-interest (ROIs) identified by measuring the downsampling distortions against the visibility thresholds given by the JND model. The coding error at any pixel location can be guaranteed to be within the corresponding JND threshold in order to obtain excellent visual quality. Experimental results show the improved accuracy of the proposed JND model in estimating visual redundancies compared with classic JND models published earlier. Compression experiments demonstrate improved rate-distortion performance and visual quality over JPEG-LS as well as reduced compressed bit rates compared with other standard codecs such as JPEG 2000 at the same peak signal-to-perceptible-noise ratio (PSPNR). FPGA synthesis results targeting a mid-range device show very moderate hardware resource requirements and over 100 Megapixel/s throughput of both the JND model and the perceptual encoder.

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