A new approach for restoring block-transform coded images with estimation of correlation matrices

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Consistent Image Decoding from Multiple Lossy Versions

With the recent development of tools for data sharing in social networks and peer to peer networks, the same information is often stored in different nodes. Peer-to-peer protocols usually allow one user to collect portions of the same file from different nodes in the network, substantially improving the rate at which data are received by the end user. In some cases, however, the same multimedia document is available in different lossy versions on the network nodes. In such situations, one may be interested in collecting all available versions of the same document and jointly decoding them to obtain a better reconstruction of the original. In this paper we study some methods to jointly decode different versions of the same image. We compare different uses of the method of Projections Onto Convex Sets (POCS) with some Convex Optimization techniques in order to reconstruct an image for which JPEG and JPEG2000 lossy versions are available

Estimated spectrum adaptive postfilter and the iterative prepost filtering algirighms

The invention presents The Estimated Spectrum Adaptive Postfilter (ESAP) and the Iterative Prepost Filter (IPF) algorithms. These algorithms model a number of image-adaptive post-filtering and pre-post filtering methods. They are designed to minimize Discrete Cosine Transform (DCT) blocking distortion caused when images are highly compressed with the Joint Photographic Expert Group (JPEG) standard. The ESAP and the IPF techniques of the present invention minimize the mean square error (MSE) to improve the objective and subjective quality of low-bit-rate JPEG gray-scale images while simultaneously enhancing perceptual visual quality with respect to baseline JPEG images

A document image model and estimation algorithm for optimized JPEG decompression

The JPEG standard is one of the most prevalent image compression schemes in use today. While JPEG was designed for use with natural images, it is also widely used for the encoding of raster documents. Unfortunately, JPEG\u27s characteristic blocking and ringing artifacts can severely degrade the quality of text and graphics in complex documents. We propose a JPEG decompression algorithm which is designed to produce substantially higher quality images from the same standard JPEG encodings. The method works by incorporating a document image model into the decoding process which accounts for the wide variety of content in modern complex color documents. The method works by first segmenting the JPEG encoded document into regions corresponding to background, text, and picture content. The regions corresponding to text and background are then decoded using maximum a posteriori (MAP) estimation. Most importantly, the MAP reconstruction of the text regions uses a model which accounts for the spatial characteristics of text and graphics. Our experimental comparisons to the baseline JPEG decoding as well as to three other decoding schemes, demonstrate that our method substantially improves the quality of decoded images, both visually and as measured by PSNR

Suppression of blocking artifact in compressed image

Image compression is actually major content for certain perspectives in the area of interactive media communication. Image processing is the mechanism for handling different kinds of images, processed images can be stored routinely and conveyance of such kind of images from one place to another place becomes simple to the user. By using image compression technique we are able to represent the image with lesser number of data bits. image compression execution can cut down the bandwidth and the volume of the data to be transmitted. (BDCT) block-based discrete cosine transform is long establish used transform for the two static and uninterrupted images. While we compress any kind of image by lossy type of image compression technique then there will be loss of data bits, we have to confrontation unwanted artifacts ringing and blocking artifacts and when we want to restore such kind of image then we face problem of blurring of images, which is sometimes called as the annoying artifacts problem near the block of the image. The recovered images from jpeg compression create blocking artifact near block boundaries of the image in high compression. Artifacts take on several forms in images. We are going to focus on blocking artifacts at medium and high level compression. Various types of images can be processed and we can diminish blocking artifacts up to tolerable level. Some standard techniques MPEG and JPEG are used in video and image processing field respectively for the compression. Lossy image compression technique is used in photographic images because loss of bits is tolerable, Since last few decades, image compression in real time applications has been a provocative field for image processing professionals. To recover original image decompression succeed by the different post processing techniques. High quality image communication with low-bit rate