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...

Image retrieval and image compression have been pursued separately in the past. Only little research has been conducted on a synthesis of the two by allowing image retrieval to be performed directly in the compressed domain of images without the need to decode them first. In this paper we introduce a novel approach that provides such midstream content access [6]. Our work is based on the Colour...

The using of characteristics of the human visual system (HVS) can significantly improve the efficiency of video coding process. Enhanced coding processes take into account the high spatial variability of HVS in sampling, coding and understanding of visual information. The highest visual sensitivity is at the point of fixation and decreases rapidly with distance from that point. Foveated image a...

image database, image retrieval, run length coding, Freeman coding, downsampling Content-based image retrieval (CBIR) is an important issue in the computer vision community. Both visual and textual content descriptions are employed when the user formulates queries. Shape feature is an important visual feature, as it corresponds to the region of interest in images. For retrieval, shape compariso...

In this paper, we propose a new postprocessing method for low bit-rate wavelet-based image coding which uses the technique of wavelet modulus maximum representation (WMMR). The edge degradation from wavelet-based coding is discussed under the overcomplete wavelet expansion, and interpreted as the distortion of wavelet modulus maxima, i.e., magnitude decays. Based on the empirical analysis and e...

Pattern recognition has emerged as an effective measure for automated system. I n such an approach the coding is carried out over a set of images and result are retrieved based on the best match approach. Where image features are taken as the representative feature for image coding, the introduced artifacts are the major effects at the coding level. In this work a shape oriented coding based on...

Recently, the sparse coding based codebook learning and local feature encoding have been widely used for image classification. The sparse coding model actually assumes the reconstruction error follows Gaussian or Laplacian distribution, which may not be accurate enough. Besides, the ignorance of spatial information during local feature encoding process also hinders the final image classificatio...

An artiicial neural network visual model is developed, which extracts multi-scale edge features from the decompressed image and uses these visual features as input to estimate and compensate for the coding distortions. This provides a generic postprocessing technique that can be applied to all the main coding methods. Experimental results involving post-processing the JPEG and quadtree coding s...

Low bit-rate image coding brings about obvious degradation to the compressed images, among which distortions at edges are particular objectionable. In this paper, a model-based edge reconstruction algorithm is proposed for wavelet-based image coding at low bitrate. Our approach applies a general model to represent varieties of edges existing in an image. Based on this model, the problem of edge...