Image Data Compression Techniques Research Articles

Hybrid Approaches to Image Coding: A Review

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 quantization. Several second generation coding schemes or the segmentation based schemes are also gaining popularity. Practically efficient compression systems based on hybrid coding which combines the advantages of different traditional methods of image coding have also being developed over the years. In this paper, different hybrid approaches to image compression are discussed. Hybrid coding of images, in this context, deals with combining two or more traditional approaches to enhance the individual methods and achieve better quality reconstructed images with higher compression ratio. Literature on hybrid techniques of image coding over the past years is also reviewed. An attempt is made to highlight the neuro-wavelet approach for enhancing coding efficiency.

Kompresi Citra Medis Menggunakan Alihragam Kosinus Diskret Dan Sistem Logika Fuzzy Adaptif

The required of bandwidth for communication of digital image data is increased. Limited channel capacity favors image compression techniques. These techniques attempt to minimize the number of bits needed to represent an image and to reconstruct it with little visible distortion. The image data compression techniques reduce memory of storage data and time needed to transmit data. One of the image data compression methods is using Discrete Cosine Transform and Adaptive Fuzzy Logic. The objective of this research is compressing medical image using Discrete Cosine Transform and Adaptive Fuzzy Logic System. Discrete Cosine Transform is applied to find the data will which be encoded and Adaptive Fuzzy Logic System is applied to classify sub image into certain class. The class classification of a sub image is according to their AC energy levels. The systems assign more bits to a sub image if the sub image contains much detail (large AC energy) and less bits if contains less detail (small AC energy). The result of the research shows that the accurate calculation of AC energy determines class classification of sub image and bitmaps used for image data compression must be matching with characteristic of image. Bitmaps used for image data compression determine compression ratio and reconstructed image quality. The medical image compression with ratio of 1:4.8028 result in a reconstruction image with SNR of 63.8197 dB, and visually shows that the image is similar to the original image without significant error.

Orthogonal wavelets in nonlinear speckle reduction for improved target recognition

We propose a novel orthogonal wavelet-based approach to reduce speckle in synthetic aperture radar and gray-scale images for better automatic target recognition applications. We also analyze different image metrics using different thresholding and image data compression techniques.

Lossy Image Compression Using Wavelets

In this paper, we report the results of the application of transform coding image data compression techniques using Daubechies and Coifman wavelets. More specifically, D2, D4, D8, D16, and C6, C12 wavelets were used. The results from these wavelets were compared with those of discrete cosine transform. They clearly demonstrated the superiority of the wavelet-based techniques both in compression ratios and image quality, as well as in computational speed. Two quantization methods were used: non-uniform scalar quantization and pseudo-quantization. Both produced satisfactory results (86–88% compression ratio, and acceptable image quality).

Discrete Cosine Transform data compression applied to satellite sensor images

Abstract Images are now widely available in the form of digital data. Unfortunately the amount of data that results from the digitization process is extremely large, resulting in high costs in terms of storage demand or transmission bandwidth for such data. Image data compression techniques are becoming widely used in order to reduce these problems, a standard technique being the Discrete Cosine Transform (DCT). Significant compression ratios are achievable using the DCT (typically 20:1), but with the drawback of some loss of accuracy in the decompressed reconstructed image. In some applications (e.g., videophone) some loss in the received data can be tolerated. The purpose of this paper is to present an assessment of the compression available when the DCT is applied to remote sensing images, and to determine the effects of data loss in terms of image fidelity and experimental multi-band classification of reconstructed image data. Results are presented to demonstrate the effects of using the DCT for remot...

Application of Optical Disks to Digital Color Video Recording

Magnetooptic disks offer many advantages such as large capacities, rewrit-ability, and random access. However, the storage capacities and data transfer rates of magnetooptic disks are not yet adequate for application in color video recording. There are two approaches to the application of magnetooptic disks to color video recording. One involves improvement of the storage capacity and data transfer rate of the magnetooptic disks; the other relies on image data compression techniques. We review stacked optical disk files and high-speed, high-density recording technologies as examples of the former approach. We then describe a multimedia filing system using stacked optical disk files, which can record and reproduce video and audio information in an integrated manner. Finally, we describe a color video data compression technique and explain the suitability of magnetooptic disks for packaged video media.

An analysis of selected computer interchange color spaces

Important standards for device-independent color allow many different color encodings. This freedom obliges users of these standards to choose the color space in which to represent their data. A device-independent interchange color space must exhibit an exact mapping to a colorimetric color representation, ability to encode all visible colors, compact representation for given accuracy, and low computational cost for transforms to and from device-dependent spaces. The performance of CIE 1931 XYZ, CIELUV, CIELAB, YES, CCIR 601-2 YCbCr, and SMPTE-C RGB is measured against these requirements. With extensions, all of these spaces can meet the first two requirements. Quantizing error dominates the representational errors of the tested color spaces. Spaces that offer low quantization error also have low gain for image noise. All linear spaces are less compact than nonlinear alternatives. The choice of nonlinearity is not critical; a wide range of gammas yields acceptable results. The choice of primaries for RGB representations is not critical, except that high-chroma primaries should be avoided. Quantizing the components of the candidate spaces with varying precision yields only small improvements. Compatibility with common image data compression techniques leads to the requirement for low luminance contamination, a property that compromises several otherwise acceptable spaces. The conversion of a device-independent representation to popular device spaces by means of trilinear interpolation requires substantially fewer lookup table entries with CCIR 601-2 YCbCr and CIELAB.

Data compression systems for home-use digital video recording

The authors focus on image data compression techniques for digital recording. Image coding for storage equipment covers a large variety of systems because the applications differ considerably in nature. Video coding systems suitable for digital TV and HDTV recording and digital electronic still picture storage are considered. In addition, attention is paid to picture coding for interactive systems, such as the compact-disc interactive system. The relation between the recording system boundary conditions and the applied coding techniques is outlined. The main emphasis is on picture coding techniques for digital consumer recording. >

Image coding based on two-channel conjugate VQ

Two-channel conjugate VQ (TCCVQ) has been recently proposed for speech coding. Compared to ordinary VQ, two-channel conjugate VQ requires less computational complexcity and less storage (memory) and is more robust against channel errors. This technique is now extended to image coding. The emphasis in this paper is on the usefulness of the TCCVQ when it is applied to image coding or is combined with a conventional image coding technique. Initial investigation confirms these advantages of two-channel conjugate VQ. For a noise-free channel the performances of both techniques are similar. However, when channel noise is injected, for the same bit rate, images reconstructed based on two-channel conjugate VQ are subjectively more pleasing (have less visible distortion) than those based on ordinary VQ. Both VQ techniques are also applied to a well-known separating mean VQ and are tested for robustness against channel errors. Computer simulations demonstrate the success of the two-channel conjugate VQ technique for image data compression at various bit rates.

Definition and evaluation of a transputer-based architecture for image compression and reconstruction

A technique for image data compression (and reconstruction) has been implemented on a transputer network. This technique developes in three phases: data decorrelatlon by Discrete Cosine Transform (DCT), quantization and Huffman coding. Two different architectural solutions are presented for the decorrelating phase, which is the higher compute intensive of the overall processing. The first one refers to the parallelism in the algorithm for the DCT, while the second one is based on the "farm processing" approach. Evaluations in terms of processing speed and efficiency are given for both these solutions.

Method of vector quantization coding using rectangular transform for image compression

First of all a simple and practical rectangular transform is given, and then the vector quantization technique which is rapidly developing recently is introduced. We combine the rectangular transform with vector quantization technique for image data compression. The combination cuts down the dimensions of vector coding. The size of the codebook can reasonably be reduced. This method can reduce the computation complexity and pick up the vector coding process. Experiments using image processing system show that this method is very effective in the field of image data compression.

講座 画像情報圧縮の手ほどき 第９回 静止画像の符号化方式

講座 画像情報圧縮の手ほどき 第９回 静止画像の符号化方式

講座 画像情報圧縮の手ほどき 第１１回 テレビ信号のアナログ帯域圧縮

講座 画像情報圧縮の手ほどき 第１１回 テレビ信号のアナログ帯域圧縮

講座 画像情報圧縮の手ほどき 第１２回 新しい画像符号化方式

講座 画像情報圧縮の手ほどき 第１２回 新しい画像符号化方式

Folding—A New Bilevel Image Data Compression Technique

The problem of two-tone image data compression is considered. A new technique that takes care of the redundancy due to symmetry in the image has been proposed for compression. The basic idea is to fold the image plane successively into pages. At each folding, maximum tie in the grey levels of the corresponding pels of the pages is ensured. For a square image, the successive folding is continued till each page of one pel size is obtained. The stack of page is then coded by run length variable length or fixed-length coding scheme. Compressibility has been demonstrated with a few examples and the results have been compared with other exact coding schcmes.

Transmission techniques for picture Prestel

The teletext and videotex systems which are in service in the UK provide a mosaic type of graphics, permitting the display of simple pictures and diagrams. However several uses for an improved graphics facility have been identified which could benefit from still colour television pictures of normal definition and gradation. An experimental system has been developed to investigate the feasibility of such a picture option for future viewdata services. Since the available data rates are rather low for picture transmission, the application of image data compression techniques is imperative for acceptable picture update times at the receiver.