Deblocking of Block-Transform Compressed Images Using Phase-Adaptive Shifted Thresholding

2008 ◽  
Author(s):  
Alexander Wong ◽  
William Bishop
Keyword(s):  
Compressed Images ◽  
Block Transform

Restoration of block-transform compressed images via homotopic regularized sparse reconstruction

2015 ◽  
Author(s):  
Jeffrey Glaister ◽  
Shahid A. Haider ◽  
Alexander Wong ◽  
David A. Clausi
Keyword(s):  
Sparse Reconstruction ◽  
Compressed Images ◽  
Block Transform

A robust and high capacity data hiding method for JPEG compressed images with SVD-based block selection and advanced error correcting techniques

2021 ◽  
pp. 1-11
Author(s):  
Kusan Biswas
Keyword(s):  
Data Hiding ◽  
High Capacity ◽  
Error Correcting Codes ◽  
Human Vision ◽  
Data Embedding ◽  
Compressed Images ◽  
Matrix Encoding ◽  
Dct Coefficients ◽  
Capacity Data ◽  
Value Decomposition

In this paper, we propose a frequency domain data hiding method for the JPEG compressed images. The proposed method embeds data in the DCT coefficients of the selected 8 × 8 blocks. According to the theories of Human Visual Systems  (HVS), human vision is less sensitive to perturbation of pixel values in the uneven areas of the image. In this paper we propose a Singular Value Decomposition based image roughness measure (SVD-IRM) using which we select the coarse 8 × 8 blocks as data embedding destinations. Moreover, to make the embedded data more robust against re-compression attack and error due to transmission over noisy channels, we employ Turbo error correcting codes. The actual data embedding is done using a proposed variant of matrix encoding that is capable of embedding three bits by modifying only one bit in block of seven carrier features. We have carried out experiments to validate the performance and it is found that the proposed method achieves better payload capacity and visual quality and is more robust than some of the recent state-of-the-art methods proposed in the literature.

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