The success of sparse representations in image modeling and recovery has motivated its use in computer vision applications. Object recognition has been effectively performed by aggregating sparse codes of local features in an image at multiple spatial scales. Though sparse coding guarantees a highfidelity representation, it does not exploit the dependence between the local features. By incorpor...

In this paper, it is considered the image compression scheme, in which a part of coded data extracted in the coding process is hidden into the other parts of coded data of own image, especially into the block address data of the best matching block within restricted blocks. The proposed scheme is able to be used in a fractal image coding in which the best matching domain block is searched, in a...

Content-aware image resizing (CAIR) is desired because it preserves prominent regions in a resized image. However, CAIR requires high computational complexity to perform in mobile devices, though it is desired for these displays. Moreover, transmitting the side information for CAIR from the encoder is a problem since it usually requires high bitrates compared with those for image data. In this ...

An investigation into the combining of image-processing schemes, specifically an image enhancement scheme, with existing compression schemes is discussed. Results are presented on the pyramid coding scheme, the subband coding scheme, and progressive transmission. Encouraging results are demonstrated for the combination of image enhancement and pyramid image coding schemes, especially at low bit...

Among other factors that characterize satellite communication channels is their high bit error rate. We present a system for still image transmission over noisy satellite channels. The system couples image compression together with error control codes to improve the received image quality while maintaining its bandwidth requirements. The proposed system is tested using a high resolution satelli...

Now a days, the digital world is most focused on storage space and speed. With the growing demand for better bandwidth utilization, efficient image data compression techniques have emerged as an important factor for image data transmission and storage. To date, different approaches to image compression have been developed like the classical predictive coding, popular transform coding and vector...

The main purpose of image compression is to use as many bits as possible to represent the source image by eliminating the image redundancy with acceptable restoration. Fractal image compression coding has achieved good results in the field of image compression due to its high compression ratio, fast decoding speed as well as independency between decoding image and resolution. However, there is ...

In this paper, a new image synthesis model based on the wavelet bases is proposed. In the proposed model, images are approximated from the sum of synthesis functions that are shifted to image edges. By applying the proposed model to sketch-based image coding, any iterative image recovery procedure is not required for image decoding. In the design of the synthesis functions, we define the synthe...

In this work, we investigate how to automatically reassign the manually annotated labels at the image-level to those contextually derived semantic regions. First, we propose a bi-layer sparse coding formulation for uncovering how an image or semantic region can be robustly reconstructed from the over-segmented image patches of an image set. We then harness it for the automatic label to region a...

A two-stage lossless image compression scheme is presented , the rst stage of which decorrelates the raw image data by using a two-dimensional, causal linear predic-tor, resulting in signiicant entropy reduction. The second stage uses standard coding techniques. Diierent two-stage schemes are compared with respect to their performances on several images, using bilevel coding, arithmetic coding,...