Efficient Image Transmission Research Articles

Unequal weighting of monocular inputs in binocular combination: Implications for the compression of stereoscopic imagery.

For efficient storage and transmission of stereoscopic images over bandwidth-limited channels, compression can be achieved by degrading 1 monocular input of a stereo pair and maintaining the other at the desired quality. The desired quality of the fused stereoscopic image can be achieved, provided that binocular vision assigns greater weight to the nondegraded input. A psychophysical matching procedure was used to determine if such over-weighting occurred when the monocular degradation included blur or blocking artifacts. Over-weighting of the nondegraded input occurred for blur, but under-weighting of the nondegraded input occurred for blockiness. Some participants exhibited ocular dominance, but this did not affect the blur results. The authors conclude that blur, but not blockiness, is an acceptable form of monocular degradation.

Arithmetic coding-based continuous error detection for efficient ARQ-based image transmission

Block cyclic redundancy check (CRC) codes are typically used to perform error detection in automatic repeat request (ARQ) protocols for data communications. Although efficient, CRCs can detect errors only after an entire block of data has been received and processed. We propose a new continuous error detection scheme using arithmetic coding that provides a novel tradeoff between the amount of added redundancy and the amount of time needed to detect an error once it occurs. This method of error detection, first introduced by Bell, Witten, and Cleary (1990), is achieved through the use of an arithmetic codec, and has the attractive feature that it can be combined physically with arithmetic source coding, which is widely used in state of-the-art image coders. We analytically optimize the tradeoff between added redundancy and error-detection time, achieving significant gains in bit rate throughput over conventional ARQ schemes for binary symmetric channel models for all probabilities of error.

An economical, personal computer-based picture archiving and communication system.

Taichung Veterans General Hospital has been developing a hospital-wide picture archiving and communication system (PACS) since 1993. A personal computer-based environment was implemented to reduce costs (only $2,500 for each view station) and take advantage of distributed system techniques. Other features of the PACS are automatic image acquisition, hierarchic storage management, efficient image transmission, robust fault tolerance, and user-friendly image manipulation. The system is integrated with the hospital information system so that Chinese-language patient data can be automatically transferred. A four-tier storage hierarchy and a multipath search strategy are used to improve reliability and efficiency. Image compression and efficient image transmission techniques (autorouting and prefetching) are used to reduce the response time. Robust fault tolerance is achieved with fault-tolerant hardware, image replication, and a system watchdog. User-friendly image manipulation features include easy adjustment of the brightness, contrast, or quality of the displayed image; several windows for image display; and image measurement capability. The PACS currently supports computed tomography, ultrasound, magnetic resonance imaging, computed radiography, and digital fluoroscopy; almost all appropriate personal computers in the hospital can be used as view stations. Users are satisfied with the quality, reliability, and performance of the system.

Mobile image transmission using combined source and channel coding with low complexity concealment

In this paper, we propose an efficient image transmission system for reliable transmission of vulnerable compressed images over mobile radio channels. The image coder is fully compatible with the JPEG baseline coding standard. Its transmission system is designed based on lossy transmission with combined source and channel coding (CSCC) and low complexity error concealment. Specifically, the proposed CSCC uses block codes which are designed to match both the coded image characteristics and wireless channel statistics, thereby accomplishing efficient transmission along with good visual quality. Together with a block-shuffling scheme, a simple error-concealment technique is introduced to effectively reconstruct the damaged image blocks caused by the residual errors. It is shown that the proposed techniques are applicable to mobile image transmission with different compression ratios under various mobile channel conditions. Performance results based on images `LENA' and `AIRPLANE', which are coded at 0.85 and 0.90 bit/pixel, respectively, under the simulated GSM channel (Pan-European Cellular Standard) with an average SNR (signal-to-noise ratio) of 18 dB and various vehicle speeds (2–50 miles/h) indicate that the proposed system achieves a throughput as high as 70% with good visual quality at PSNRs (peak signal-to-noise ratio) around 30 dB for the reconstructed images.

A neural synaptic compression codec for efficient image transmission

For efficient cellular communication channel usage, we propose a neural computation model for image coding. In a constant-time unsupervised learning, our neural model approximates optimal pattern clustering from training example images through a memory adaptation process, and builds a compression codebook in its synaptic weight matrix. This neural codebook can be distributed to both ends of a transmission channel for fast codec operations on general images. The transmission is merely the indices of the codebook entries best matching the patterns in the image to be transmitted. These indices can further be compressed through a classical entropy coding method to yield even more transmission reduction. Other advantages of our model are the low training time complexity, high utilization of neurons, robust pattern clustering capability, and simple computation. A VLSI implementation is also highly suitable for the intrinsic parallel nature of neural networks. Our compression results are competitive compared to JPEG and wavelet methods. We also reveal the general codebook's cross-compression results, filtering effects by special training methods, and learning enhancement techniques for obtaining a compact codebook to yield both high compression and picture quality.

Thermal images generated by a line-scanning technique: statistical properties

The analysis of statistical parameters of computer-generated therfial images by a line-scanning technique indicates an approach to efficient image transmission.

Optical elements for efficient one-dimensional image transmission through a single multimode fiber

Optical elements, including continuous surface and multiple-ring types, are considered to improve the efficiency of one-dimensional imaging by angular multiplexing in a single multimode fiber. The limiting resolution of the multiple-ring method, determined by ring width, fiber diameter, etc., is discussed. Results are presented for a holographic implementation, with up to ten concentric rings, operating in monochromatic light. The use of computer-generated holograms is suggested.

Nonlinear image processing for optimum composite source coding

The concept of composite source coding for efficient image transmission or storage is addressed in the paper, and specific properties characterising the component sources are determined. An approach is developed which decomposes typical image signals into two independent additive components. Each component is subsequently encoded separately for storage or transmission. These individual components are combined at the receiver (or recovery stage) to produce a replica of the original signal. Special attention is focused on the optimality of the signal partitioning in the sense that the rate required to transmit the two components is minimum for a priori specified values of the average distortion in the reconstruction of the original signal. A formulation of the mathematical problem is effected in such a way that nonlinear techniques based on dynamic programming are used to achieve efficiently the optimum partitioning. Of the two components, only one is allowed a certain but controllable degree of degradation for the purpose of transmission rate reduction. The other component, which is associated with certain perceptually essential image features, is transmitted without distortion. The subjective quality of the reconstructed image is thereby preserved without incurring further increase in the total transmission rate.

New bounds to R(D) for additive sources and applications to image encoding

In order to apply the results of information theory to the efficient storage or transmission of images, it is necessary to model the image source distribution and specify an appropriate fidelity criterion. One useful source model results from separating the log intensity random field of a typical image into the sum of two nearly independent random fields with a simpler description. It has also been found that under certain conditions a frequency-weighted squared-error fidelity criterion is satisfactory for evaluating the images. Thus it is important to consider the situation in which the source output is the sum of two independent random entities with known rate-distortion functions with respect to a (perhaps frequency-weighted) squared-error criterion. These rate-distortion functions are used to provide new bounds to the rate-distortion function of the additive source with respect to the same criterion. In one example considered, the new bounds are the tightest known in certain distortion regions. Examples from image coding are given, including a comparison of the performances of various encoding schemes.

Adaptive block scheme for source coding of black-and-white facsimile

A simple adaptive block coding method is proposed which could be useful for efficient transmission or storage of 2-level images (black-and-white facsimile). A comparison of this autoadaptive technique with optimum run-length coding and nonadaptive block coding shows that a significant improvement in redundancy reduction can generally be obtained.