Images In Discrete Cosine Transform Domain Research Articles

Image representation using block compressive sensing for compression applications

The emerging compressive sensing (CS) theory has pointed us a promising way of developing novel efficient data compression techniques, although it is proposed with original intention to achieve dimension-reduced sampling for saving data sampling cost. However, the non-adaptive projection representation for the natural images by conventional CS (CCS) framework may lead to an inefficient compression performance when comparing to the classical image compression standards such as JPEG and JPEG 2000. In this paper, two simple methods are investigated for the block CS (BCS) with discrete cosine transform (DCT) based image representation for compression applications. One is called coefficient random permutation (CRP), and the other is termed adaptive sampling (AS). The CRP method can be effective in balancing the sparsity of sampled vectors in DCT domain of image, and then in improving the CS sampling efficiency. The AS is achieved by designing an adaptive measurement matrix used in CS based on the energy distribution characteristics of image in DCT domain, which has a good effect in enhancing the CS performance. Experimental results demonstrate that our proposed methods are efficacious in reducing the dimension of the BCS-based image representation and/or improving the recovered image quality. The proposed BCS based image representation scheme could be an efficient alternative for applications of encrypted image compression and/or robust image compression.

Multi-channel watermarking scheme based on HVS for color image in DCT domain

A blind watermarking algorithm for digital image based on Discrete Cosine Transform (DCT) was proposed. First,the original image was transformed from RGB color space into YCbCr color space,which has excellent independence of every channel,and then the watermarking was embedded into all three color spaces. Secondly,the watermarking was embedded by image watermarking technique of DCT,and the embedding capacity depended on Human Visual System (HVS). The experimental result indicates that the algorithm is visually imperceptible and robust to general image processing.

Arbitrary resizing of images in DCT domain using lapped transforms

An arbitrary L/M-fold image resizing method using lapped transforms is presented. The resizing operation is carried out in the lapped transform domain, by converting the images in the discrete cosine transform (DCT) domain into those in the lapped transform domain and vice versa. The proposed method provides visually fine images, while reducing the blocking effect to a very low level for images compressed at low bit rates.