Coded Image Data Research Articles

Performance Analysis of Regular and Irregular LDPC Codes on SPIHT Coded Image Data

The LDPC (Low Density Parity Check Code) has Shown interesting results for transmitting embedded bit streams over noisy communication channels. Performance comparison of regular and irregular LDPC codes with SPIHT coded image is done here. Different Error Sensitive classes of image data are obtained by using SPIHT algorithm as an image coder. Irregular LDPC codes map the more important class of data into a higher degree protection class to provide more protection. Different degree protection classes of an LDPC code improves the overall performance of data transmission against channel errors. Simulation results show the superiority of irregular LDPC over regular LDPC codes.

An efficient hierarchical 16‐QAM dynamic constellation to obtain high PSNR reconstructed images under varying channel conditions

Startling growth in multimedia services over wireless channels emphasizes the need for bandwidth and power efficient modulation techniques. This study investigates the suitability of hierarchical quadrature amplitude modulation (HQAM) for image transmission over erroneous wireless Gaussian channels. HQAM provides unequal error protection, to compressed and coded image data, transmitted without increasing the required bandwidth, unlike channel coding. A discrete cosine transform based image coder is used to divide the image data bit stream into high-priority (HP) and low-priority (LP) sub-streams for significant and non-significant data respectively. The ratios between the constellation distances are then dynamically adjusted with the objective to achieve an acceptable bit-error rate (BER) for HP sub-stream over varying channel conditions at the cost of increased BER for LP sub-stream. The work highlights HQAM implementation using conventional quadrature amplitude modulation (QAM) demodulator at the receiver which does not require the knowledge of varying constellation distance ratios at the transmitter. An analysis of 16-HQAM transmission for different values of distance ratios is presented to obtain high peak signal-to-noise ratio (PSNR) values of reconstructed images under poor as well as good channel conditions and the performance is compared qualitatively and quantitatively with 16-QAM.

Evaluating Instantaneous Psychological Stress from Emotional Composition of a Facial Expression

Human psychological stress is a vast and highly complicated topic of study and research. The types and kinds of stress observed in humans vary among researchers. Also, to identify stress, many methods exist. Most of these methods are non-intrusive and are based on self-reporting and questionnaires which reduces the real-time efficacy of the procedure. Intrusive methods are, on the other hand, time consuming and cumbersome. The total problem of non-intrusive psychological stress detection from facial images can be visualized in three incremental stages: instantaneous analysis of subject, historical analysis of subject, and the subject’s environmental analysis. In this paper, we deal with instantaneous analysis of a subject. This means that the stress behavior of a subject is predicted for one moment of time using an image of his/her facial expression. In order to do so, we have conducted two surveys to establish the relationship between emotional compositions of a facial expression with stress and also to establish the relationship of individual emotions with stress. The novelty of the paper is 1) to establish relationships between the seven basic emotions (anger, contempt, disgust, fear, happy, sad, and surprise) and stress, 2) to establish relationship between emotional composition of a facial expression and stress, and 3) to predict a formula for evaluating stress in terms of emotional percentage mixture of a facial expression. In order to achieve the three goals, we use Facial Action Unit (AU) [1] coded image data to predict the emotional mixture of the facial expression in terms of the seven basic emotion percentages. An AU represents one of the many basic muscle movements that make up the facial expression. Then we analyze the survey outcomes to establish the relationship between individual emotions and stress. Finally we correlate the survey outcomes with the emotional mixture data obtained from the facial expression using Hidden Markov Model (HMM) approach to both establish a relationship of emotional composition with stress and to predict a formula for stress in terms of the seven basic emotion percentages jointly.

The Implement of MPEG-4 Video Encoding Based on NiosII Embedded Platform

Using software code to achieve video coding, reduce the cost and increase portability, present a scheme using Altera SOPC to control data coding for MPEG-4 video software compressing system. According to use the DE2 board of Altera, implementing coding image data’s input and output through the USB port on the board, achieves the input image MPEG-4 encoding using the configural NiosII embedded soft processor. Aiming at MPEG-4 video compression, the design adopts dynamic sprite encode to code the image data efficiently.

Shot change detection from MPEG encoded video data

In matching and browsing of video images, it is important that their shot changes are detected efficiently. The detection of shot changes without decoding image data has actively been studied recently, since this is cost effective. However, in conventional methods, noise (e.g., a flash, or a sudden motion) in an image is often erroneously recognized as shot changes, and these reduce the “precision rate;” in addition, slow shot-changes (order of a unit field) are difficult to detect, and they reduce the “recall rate.” This paper proposes an accurate and fast method of counting shot changes in MPEG coded image data. As an example of application of the method, this paper describes a hybrid MPEG browser which recognizes the contents of the images. © 2000 Scripta Technica, Syst Comp Jpn, 31(2): 40–48, 2000

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).

A Study on Camera Work Extraction Technology from Compressed Image Information.

It is important to structure video sequences for efficiently editing and indexing the images that may be requested from an enormous volume of video data. One approach to structuring is to divide a series of images into fixed units such as cut points or camera work, and then retrieving against the units. This paper proposes a method of automatically extracting camera work sequences. Specifically, in this paper, MPEG2, which can be mainstream in future, coded video data is targeted. To reduce the volume of data to be processed, to eliminate the time need for decoding, and to avoid video loss due to decoding, we estimate the camera work using the extracted motion vectors which used in the motion compensation process. The proposed method extracts the motion vectors using motion compensation. To recognize the camera work in each frame, we also present an algorithm for extracting each camera work sequence. The efficiency of the method is confirmed using MPEG2 coded image data of diverse test video sequences.

A 2-D vector excitation coding technique

We present a VQ-based technique for coding image data that adopts an analysis by synthesis approach. We define a new type of spatial interaction model for image data, called prediction pattern, which we use along with a excitation vector, to generate an approximation of an input block of pixels. A prediction pattern is a k× k array with each element representing a prediction scheme from a given set of predictors. A prediction pattern captures the spatial dependences present in an image block. Given a codebook of prediction patterns and a codebook of excitation vectors, we encode an image by partitioning it into blocks and for each block identifying the prediction pattern from within the codebook that best models the spatial dependences that are present in the block. We then search the excitation codebook for a code vector that in combination with the already chosen prediction pattern results in the synthesis of the closest approximation to the current image block. We present algorithms for codebook design and give implementation results. The proposed technique gives promising results.

Morphological Operations for Color‐Coded Images

AbstractThe subject of this paper is the semantically based postprocessing of color–coded images such as classification results. We outline why the classical definition of mathematical morphology suffers if it is used for processing of coded image data. Therefore we provide an extension for morphological operations such as dilation, erosion, opening, and closing. With a new understanding of morphology we introduce bridging and tunneling as further combinations of dilation and erosion. The extensions are applied to medical image data, where the semantic rules stem from basic anatomical knowledge.

Haar wavelet transform with interband prediction and its application to image coding

AbstractAlthough the discrete cosine transform (DCT) and wavelet transform have been used as effective techniques for reducing the redundancy of image waveforms, they have the problems of high complexity and causing block distortion. In this paper, a Haar wavelet transform with interband prediction is proposed that permits high‐speed processing and which is suitable for coding as a subband decomposition technique since it generates little block distortion in the decoded images. the interband prediction method of this proposed transform method uses the derivative of the low‐band waveform to predict the high‐band waveform each time a band is split into two sub‐bands. This results in a transform process that gives a prediction residual signal with lower entropy. During the inverse transform, the prediction coefficients obtained from the forward transform are used to predict the high‐frequency waveforms and then, by adding the prediction residual, the original high frequency waveforms are reconstructed. Because the high‐frequency waveforms are generated that smoothly interpolate the up‐sampled, low‐frequency waveforms, any block effects from this prediction technique are difficult to see in the decoded image. A detailed analysis of the proposed interband prediction process is performed by interpreting the proposed transform as a subband decomposition process that is based on the use of a symmetric short‐kernel filter (SSKF) filter bank; then experiments are conducted that demonstrate its performance as a subband decomposition for coding of real image data and the possibility of progressive build‐up of the decoded images. Results show that this transform method is effective for coding image data.

Effect of channel errors on source coded image data and the provision of adequate protection of transmission bits

The effects of channel errors on image data coded by means of a zonal transform coder and a threshold transform coder have been studied and experimental results obtained. These form the basis for the selection of a suitable error protection technique. The results have been used in conjunction with five error protection schemes as follows:(i) parameter adjustments only(ii) equal importance protection through Hamming block coding(iii) equal importance protection through Hagelbarger convolutional coding(iv) percentage subimage protection (SIP) using Hamming block codes(v) Percentage subimage protection (SIP) using Hagelbarger convolutional codes.These schemes were selected to provide continuity from one to the next, thus helping in the observation of various trade-offs in the characteristics of the overall transmission systems. A sixth scheme is proposed which turns attention away from the more trditional methods of error protection. This scheme involves maximum likelihood decoding of the Huffman coded image, and thus it can only be applied to codes of the threshold transform type. Although this scheme gives a much improved error protection, its main disadvantage is that it requires considerable data storage and significant search times when decoding the data.The results have been used to deduce the best system for transmission of source coded image data over a channel with a specified error rate and to indicate the preferred technique for the protection of the data.

An msm coding of a binary image and an msm figure‐file system

AbstractResearches on the coding and filing of such binary image data as versatile links of drawings or topographical maps have been conducted widely [5 ‐ 19]. The reasons for this activity are tied to the advances made in techniques for processing topographical information [1, 2], automatic drawing reading [3], and image datebases [4].These techniques are aimed at high‐density compressions in image coding, but especially at greater flexibility in figure reconstruction. Additionally, some of these techniques have found practical application in such commercial areas as image databases of topographical maps or drawings or visual communications by facsimile.However, these techniques are difficult when using coding image data to obtain such flexible image processings as skeletonization or border following of figures, the detection of width or branch points of line figures, or structural analysis of line or surface drawings. As a result, this paper proposes an MSM figure‐file system which codes a binary image via the MSM method and files it as a figure, and retrieves figure data from the file.

Application of Simulated Annealing to Coded-Aperture Design and Tomographic Reconstruction

Reconstructions from coded-image data obtained with the simulated annealing algorithm are presented along with an experiment testing the effects of annealing. An efficient perturbation method for system optimization is defined, and the role of simulated annealing in such an optimization is discussed.