Compressed Color Research Articles

Lossy Compression Color Medical Image Using CDF Wavelet Lifting Scheme

Lossy Compression Color Medical Image Using CDF Wavelet Lifting Scheme

Remote Dynamic Three-Dimensional Scene Reconstruction

Remote dynamic three-dimensional (3D) scene reconstruction renders the motion structure of a 3D scene remotely by means of both the color video and the corresponding depth maps. It has shown a great potential for telepresence applications like remote monitoring and remote medical imaging. Under this circumstance, video-rate and high resolution are two crucial characteristics for building a good depth map, which however mutually contradict during the depth sensor capturing. Therefore, recent works prefer to only transmit the high-resolution color video to the terminal side, and subsequently the scene depth is reconstructed by estimating the motion vectors from the video, typically using the propagation based methods towards a video-rate depth reconstruction. However, in most of the remote transmission systems, only the compressed color video stream is available. As a result, color video restored from the streams has quality losses, and thus the extracted motion vectors are inaccurate for depth reconstruction. In this paper, we propose a precise and robust scheme for dynamic 3D scene reconstruction by using the compressed color video stream and their inaccurate motion vectors. Our method rectifies the inaccurate motion vectors by analyzing and compensating their quality losses, motion vector absence in spatial prediction, and dislocation in near-boundary region. This rectification ensures the depth maps can be compensated in both video-rate and high resolution at the terminal side towards reducing the system consumption on both the compression and transmission. Our experiments validate that the proposed scheme is robust for depth map and dynamic scene reconstruction on long propagation distance, even with high compression ratio, outperforming the benchmark approaches with at least 3.3950 dB quality gains for remote applications.

Chaos-based partial encryption of SPIHT coded color images

An embedded partial encryption technique of compressed color images based on chaos is proposed. Modifying the bit values of different types which are obtained by Color-SPIHT (CSPIHT) compression algorithm leads to varying degradation degree of retrieved images. This signifies that the six bit types have various contributions to decoding. As long as the most important bits that have the greatest contribution are encrypted, we can ensure no information leaking out and minimal computation. The piecewise linear chaotic map (PWLCM) is appropriate for generating random number sequence used in proposed cryptosystem for its perfect ergodicity and confusion. Thorough performance and security analysis as regards to diverse evaluation metrics ascertains that the scheme has less computational amount than 0.49%, resists against common cryptanalytic attacks, and preserves the scalability property of the encoder.

Novel Software Strategy for Glaucoma Diagnosis

The benefits of high-speed, detailed retinal thickness measurement by spectral-domain optical coherence tomography in glaucoma diagnosis have not been fully realized. We have modified the software protocols for such measurement and applied it for diagnosis at different stages of glaucoma. Using the Spectralis SD-OCT (Heidelberg Engineering, Carlsbad, California), we have customized the retinal thickness protocol to acquire detailed retinal thickness measurements of the central 20° of the posterior pole. These custom maps are displayed in a compressed color scale that reveals small losses in retinal thickness. A novel asymmetry analysis protocol was created to highlight differences between the eyes and the 2 hemispheres within each eye. We present case examples illustrating the ability of this strategy to detect glaucomatous defects, showing the promise of the protocol in the diagnosis and management of glaucoma.

Tone mapping using color correction function and image decomposition in high dynamic range imaging

In this paper, we propose a tone mapping (TM) method using color correction function (CCF) and image decomposition in high dynamic range (HDR) imaging. The CCF in the proposed TM is derived from the luminance compression function with the color constraint under which the color ratios, between the three color channels of the radiance map and dynamic range compression term, are preserved and color saturation is controlled. The proposed CCF is developed to locally perform the luminance compression and color saturation control in local TM. For image decomposition, we use a bilateral filter and apply the adaptive weight to the base layer of the luminance. Computer simulations with various sets of real, low dynamic range images show the effectiveness of the proposed TM algorithm in terms of the visual quality as well the local contrast. It can be used for contrast and color enhancement in various display and acquisition devices.

Local MAP estimation for quality improvement of compressed color images

This paper concerns color image restoration aiming at objective quality improvement of compressed color images in general rather than merely artifact reduction. In compressed color images, colors are usually represented by luminance and chrominance components. Considering characteristics of human vision system, chrominance components are generally represented more coarsely than luminance component. To recover such chrominance components, we previously proposed a model-based chrominance restoration algorithm where color images are modeled by a Markov random field. This paper presents a color image restoration algorithm derived by the MAP estimation, where all components are totally estimated. Experimental results show that the proposed restoration algorithm is more effective than the previous one.

A comparative study of preprocessing mismatch effects in color image based face recognition

Face color information can play an important role in face recognition (FR) and it can be used to considerably improve FR performance obtained using only grayscale images. The color-based FR methods involve a preprocessing step where a color image is converted into either a monochromatic image or an image having a different color representation. In practical FR systems, the recording or transmission format of the testing images may be arbitrary or inconsistent depending on the application (e.g., face images could consist of grayscale or color pixels either in compressed or uncompressed form). Further, a wide variety of grayscale and color conversions can be used in the preprocessing step. This could lead to a so-called preprocessing mismatch in color-based FR methods: the training and testing face images, generated after preprocessing, do not match in terms of their degree of compression or in terms of their grayscale or color representations. In contrast to grayscale-based FR, a practical color-based FR system has a higher chance of being confronted with a preprocessing mismatch. The aim of this paper is to present a comparative study that addresses the impact of a preprocessing mismatch on color-image based FR methods. We explore three different types of preprocessing mismatches, which practical color-based FR system are highly likely to encounter. In addition, comparative and extensive experiments have been carried out to analyze the effects of the preprocessing mismatches on an FR performance, using Color FRETET, CMU-PIE, AR, and SCface public face databases. The important conclusions drawn from our experiments include: (1) of all color-based FR methods under consideration, color-based FR using feature-level fusion is the most robust approach to preprocessing mismatches; (2) the preprocessing mismatch caused by the use of compressed color images can significantly deteriorate FR performance of color-based FR methods; (3) grayscale testing images can be critical for the feasibility of color-based FR using an input-level fusion; (4) the preprocessing mismatch in terms of grayscale representation has little effect on the FR performances of color-based FR methods.

Quality access control of compressed color images using data hiding

This paper proposes a scheme for quality access control of discrete cosine transform ( DCT) based compressed color image(s) using data hiding. The goal of access control is achieved by transforming the original image into the luminance, chrominance-blue and chrominance-red ( YC b C r ) color space followed by modulating the coefficients of luminance ( Y) and/or chrominance-red ( C r ) channels. The amount of modulation and the information about the specific channels to be modulated are contained in a key K, which is supplied by the owner/service provider. This key and the original image are used to create a content dependent key. The content dependent key is then embedded into the chrominance-blue ( C b ) component as watermark using spread spectrum modulation. This watermark information is used for demodulation that leads to the access control through the restoration of the relative quality of the images. Simulation results show that the proposed scheme provides an effective quality access control for the compressed color image without decreasing the compressibility of the standard JPEG coding scheme. The performance of the proposed method is also compared with the few other methods.

ROI Based Quality Access Control of Compressed Color Image using DWT via Lifting

ROI (Region of Interest) in an image or video signal contains important information and may be used for access control at various qualities using multiresolution analysis (MRA). This paper proposes quality access control method of compressed color image by modulating the coefficients of ROI at various levels. Data modulation causes visual degradation in the original image and plays the key role in access control through reversible process. The modulation information, in the form of a secret key, is embedded in non-ROI part of the chrominance blue (Cb) channel of the color image using quantization index modulation (QIM). Lifting based DWT, rather than conventional DWT, is used to decompose the original image in order to achieve twofold advantages of (1) low loss in image quality due to QIM and (2) better decoding reliability. Only the authorized user having the full knowledge of the secret key restores the full quality of ROI. Simulation results duly support this claims.

Motion estimation based color transfer and its application to color video compression

In this paper a novel scheme for color video compression using color transfer technique is proposed. Towards this, a new color transfer mechanism for video using motion estimation is presented. Encoder and decoder architectures for the proposed compression scheme are also presented. In this scheme, compression is achieved by firstly discarding chrominance information for all but selected reference frames and then using motion prediction and discrete cosine transform (DCT) based quantization. At decompression stage, the luminance-only frames are colored using chrominance information from the reference frames applying the proposed color transfer technique. To integrate color transfer mechanism with hybrid compression scheme a new color transfer protocol is defined. Both compression scheme and color transfer work in YCbCr color space.

NNIC—neural network image compressor for satellite positioning system

We have developed an algorithm, based on novel techniques of data compression and neural networks for the optimal positioning of a satellite. The algorithm is described in detail, and examples of its application are given. The heart of this algorithm is the program NNIC—neural network image compressor. This program was developed for compression color and grayscale images with artificial neural networks (ANNs). NNIC applies three different methods for compression. Two of them are based on neural networks architectures—multilayer perceptron and kohonen network. The third is based on a widely used method of discrete cosine transform, the basis for the JPEG standard. The program also serves as a tool for determining numerical and visual quality parameters of compression and comparison between different methods. A number of advantages and disadvantages of the compression using ANNs were discovered in the course of the present research, some of them presented in this report. The thrust of the report is the discussion of ANNs implementation problems for modern platforms, such as a satellite positioning system that include intensive image flowing and processing.

Exposing digital forgeries in color filter array interpolated images

With the advent of low-cost and high-resolution digital cameras, and sophisticated photo editing software, digital images can be easily manipulated and altered. Although good forgeries may leave no visual clues of having been tampered with, they may, nevertheless, alter the underlying statistics of an image. Most digital cameras, for example, employ a single sensor in conjunction with a color filter array (CFA), and then interpolate the missing color samples to obtain a three channel color image. This interpolation introduces specific correlations which are likely to be destroyed when tampering with an image. We quantify the specific correlations introduced by CFA interpolation, and describe how these correlations, or lack thereof, can be automatically detected in any portion of an image. We show the efficacy of this approach in revealing traces of digital tampering in lossless and lossy compressed color images interpolated with several different CFA algorithms.

Color image enhancement using a multiple-scale opponent neural network

One goal of image processing is to recreate the human visual perception of the original scene. We offer a method of color image enhancement for realistic image display. The algorithm is based on a special implementation of the feed-forward ON-OFF shunting neural network. The properties of the neural network for image processing are first investigated. The computational simulations make clear the strengths and weaknesses of the neural network. Combined with a brightness-based tone reproduction operator, a multiscale extension to the neural network is developed to correct the original version's weaknesses and provides a coherent framework for color image enhancement. The algorithm achieves both dynamic range compression and vivid color rendition and qualitatively approaches the aspects of early visual perception. Extensive tests demonstrate that this method could produce satisfying images without any unexpected results.

Artifact reduction of compressed color images using modified mean‐removed classified vector quantization

In this paper, a new artifact reduction algorithm for compressed color images using MMRCVQ is proposed. The algorithm extends and modifies vector quantization (VQ) for discovering the relationships between the uncompressed color images and their deblocked compressed versions by classifying the deblocked compressed blocks into several categories using information from their neighboring blocks. The discovered relationships are stored in two codebooks and are used to recover the missing information of compressed color images. To increase the availability of codewords and reduce the memory needed for storing codewords, mean‐removed vectors are used to generate codebooks. The experimental results show that the proposed approach can remove, effectively, the artifacts caused by high compression and improve perceptual quality significantly. Compared to existing methods, the proposed approach usually uses much less computing time to recover a compressed color image and has much better image quality.

Lattice Algorithms for Compression Color Space Estimation in JPEG Images

JPEG (Joint Photographic Experts Group) is an international standard to compress and store digital color images [5]. Given a color image that was previously JPEG-compressed in some hidden color space, we aim to estimate this unknown compression color space from the image. This knowledge is potentially useful for color image enhancement and JPEG re-compression.JPEG operates on the discrete cosine transform (DCT) coefficients of each color plane independently during compression. Consequently, the DCT coefficients of the color image conform to a lattice structure. We exploit this special geometry using the lattice reduction algorithm from number theory and cryptography to estimate the compression color space. Simulations verify that the proposed algorithm yields accurate compression color space estimates.

Appendicitis at the millennium.

Acute appendicitis is a common clinical problem. Accurate and prompt diagnosis is essential to minimize morbidity. While the clinical diagnosis may be straightforward in patients who present with classic signs and symptoms, atypical presentations may result in diagnostic confusion and delay in treatment. Helical computed tomography (CT) and graded compression color Doppler ultrasonography (US) are highly accurate means of establishing the diagnosis. These imaging modalities have now assumed critical roles in the treatment of patients suspected to have appendicitis. The purpose of this article is threefold: to provide an update on new information regarding the pathophysiology, clinical diagnosis, and laparoscopic treatment of acute appendicitis; to describe the state-of-the art use of CT and US in diagnosing this disease entity; and to address the role of medical imaging in this patient population.

Research note: a multidimensional scaling comparison of color metrics for response times and rated dissimilarities.

Individual-differences multidimensional scaling was applied to a set of proximity data for equiluminant lights (Paramei & Cavonius, 1999) to explore any differences between two data collection procedures (rated dissimilarities, and same/different response times [RTs]), as well as between color-normal and abnormal observers. Two conclusions emerged: (1) The pattern of similarities from observers with anomalous color vision can be understood in terms of a compressed color plane (the weighted Euclidean model of individual differences); and (2) there is evidence that the color "plane" is either curved or governed by a non-Euclidean distance function. When color-normal observers are examined in the weighted-Euclidean framework, minor differences emerge between RT and rating data. But the main distinguishing feature of RT data is a pattern of decreasing accuracy for larger color distances. This must be taken into account, since it can itself induce curvature.

Color Doppler sonography of focal gastrointestinal lesions: initial clinical experience.

Graded compression color Doppler sonography was used to evaluate gastrointestinal blood flow in 20 normal fasting subjects and 32 patients with focal gastrointestinal lesions. Imaging was optimized for color sensitivity using a 5 MHz linear array transducer. Criteria were established for normal mural blood flow based on findings in normal controls. Two reviewers blinded to the final diagnosis compared patterns of mural vascularity in normal and abnormal patients. Increased mural blood flow was demonstrated in all 32 patients with gastrointestinal inflammatory disorders and in seven of nine patients with neoplasms. No mural flow was demonstrated in four patients with small bowel infarction. The greatest overall degree of flow was noted in patients with Crohn's disease and cytomegalovirus colitis. Flow in tumors was variable, ranging from strikingly increased flow in a giant villoglandular polyp to absent flow in a metastasis from lung carcinoma. Our preliminary experience suggests that the presence of considerable overlap in the color Doppler patterns of mural blood flow in inflammatory and neoplastic lesions. Color Doppler sonography alone without spectral waveform analysis may not distinguish focal inflammatory from neoplastic disorders of the gastrointestinal tract reliably. However, this technique potentially may be useful in diagnosing small bowel ischemia when thickened segments of small bowel are identified with absent flow.

CD-ROM player for business presentations

A portable CD-ROM player with compressed color graphics and sound was developed. The CD-ROM player, which provides a synchronized presentation function and a hyperlinked database function, is a personal multimedia tool for business presentations and educational publications. >

Prevalence of Local Venous Thrombosis after Transfemoral Placement of a Bird's Nest Vena Caval Filter

Bird's Nest vena caval filters were placed in 63 patients over a 6-month period by means of a transfemoral (n = 62) or transjugular (n = 1) approach. To determine the prevalence of access-site thrombosis, compression color Doppler flow imaging was performed 1-11 days after the procedure in 48 patients without suspected or documented preexisting thrombus. Clinical follow-up was from 5 to 289 days (mean, 100 days). Findings at ultrasound (US) examination were normal in 38 patients, and all of these patients remained clinically asymptomatic. Nonocclusive thrombus was seen in nine patients, eight of whom remained asymptomatic. A single patient had an occlusive thrombus at US. This patient had leg swelling. Nonocclusive thrombus did not predispose patients to the development of clinically evident occlusive thrombosis. The authors conclude that the transfemoral placement of the Bird's Nest vena caval filter is associated with a low prevalence (2%) of femoral vein occlusion documented at US follow-up. This contrasts with results from a similarly designed study demonstrating a 17% prevalence after percutaneous Greenfield filter placement.