Simultaneous coding artifact reduction and sharpness enhancement for block-based compressed images and videos

2008 ◽  
Vol 23 (6) ◽  
pp. 463-470 ◽  
Author(s):  
Ling Shao
Keyword(s):  
Artifact Reduction ◽  
Compressed Images ◽  
Sharpness Enhancement ◽  
Block Based

scholarly journals Adaptive Fuzzy Filtering for Artifact Reduction in Compressed Images and Videos

2009 ◽  
Vol 18 (6) ◽  
pp. 1166-1178 ◽  
Author(s):  
Dung T. Vo ◽  
Truong Q. Nguyen ◽  
Sehoon Yea ◽  
Anthony Vetro
Keyword(s):  
Artifact Reduction ◽  
Adaptive Fuzzy ◽  
Compressed Images

Blocking artefact detection in block-based DCT compressed images

2011 ◽  
Vol 4 (3) ◽  
pp. 181
Author(s):  
Jagroop Singh ◽  
Sukhwinder Singh ◽  
Dilbag Singh ◽  
Moin Uddin
Keyword(s):  
Compressed Images ◽  
Artefact Detection ◽  
Block Based

Block-based manipulations on transform-compressed images and videos

1998 ◽  
Vol 6 (2) ◽  
pp. 113-124 ◽  
Author(s):  
Bo Shen ◽  
Ishwar K. Sethi
Keyword(s):  
Compressed Images ◽  
Block Based

scholarly journals A Novel Image Highly Compression Technique With Spread Parameter

2013 ◽  
pp. 196-199
Author(s):  
E. Wilvathi ◽  
M. KOTESWARA RAO
Keyword(s):  
Artifact Reduction ◽  
Fuzzy Filter ◽  
Linear Filtering ◽  
Linear Filters ◽  
Compression Technique ◽  
Jpeg Images ◽  
Compressed Images ◽  
Non Linear ◽  
Edge Based ◽  
Filtering Techniques

A novel image highly compressed technique has been introduced to reduce the artifacts in compressed JPEG images. In order to reduce the noise, non-linear filtering techniques are often employed than linear filters and don’t degrade the edges. A new metric has been introduced to reduce the artifacts occurred in colored images along the sharp transitions using directional spread parameter. Simulations on compressed images show improvement in artifact reduction by using edge based directional fuzzy filter when compared to the non-linear filters.

scholarly journals SCENet: Secondary Domain Intercorrelation Enhanced Network for Alleviating Compressed Poisson Noises

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1939 ◽  
Author(s):  
Seok Bong Yoo ◽  
Mikyong Han
Keyword(s):  
Noise Reduction ◽  
Image Coding ◽  
Deep Neural Network ◽  
State Of The Art ◽  
Poisson Noise ◽  
Art Restoration ◽  
Compressed Images ◽  
Coding Systems ◽  
Satisfactory Performance ◽  
Block Based

In real image coding systems, block-based coding is often applied on images contaminated by camera sensor noises such as Poisson noises, which cause complicated types of noises called compressed Poisson noises. Although many restoration methods have recently been proposed for compressed images, they do not provide satisfactory performance on the challenging compressed Poisson noises. This is mainly due to (i) inaccurate modeling regarding the image degradation, (ii) the signal-dependent noise property, and (iii) the lack of analysis on intercorrelation distortion. In this paper, we focused on the challenging issues in practical image coding systems and propose a compressed Poisson noise reduction scheme based on a secondary domain intercorrelation enhanced network. Specifically, we introduced a compressed Poisson noise corruption model and combined the secondary domain intercorrelation prior with a deep neural network especially designed for signal-dependent compression noise reduction. Experimental results showed that the proposed network is superior to the existing state-of-the-art restoration alternatives on classical images, the LIVE1 dataset, and the SIDD dataset.

scholarly journals Adaptive Fuzzy Filtering for Artifact Reduction in Compressed images and videos

2011 ◽  
Vol 3 (1) ◽  
pp. 118-137
Author(s):  
P Ramakrishna Rao ◽  
B Addai ◽  
G Ramakrishna ◽  
T PanduRanga Vital
Keyword(s):  
Artifact Reduction ◽  
Adaptive Fuzzy ◽  
Compressed Images
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