Showing papers by "William A. Pearlman published in 2004"

Efficient, low-complexity image coding with a set-partitioning embedded block coder

Abstract: We propose an embedded, block-based, image wavelet transform coding algorithm of low complexity. It uses a recursive set-partitioning procedure to sort subsets of wavelet coefficients by maximum magnitude with respect to thresholds that are integer powers of two. It exploits two fundamental characteristics of an image transform-the well-defined hierarchical structure, and energy clustering in frequency and in space. The two partition strategies allow for versatile and efficient coding of several image transform structures, including dyadic, blocks inside subbands, wavelet packets, and discrete cosine transform (DCT). We describe the use of this coding algorithm in several implementations, including reversible (lossless) coding and its adaptation for color images, and show extensive comparisons with other state-of-the-art coders, such as set partitioning in hierarchical trees (SPIHT) and JPEG2000. We conclude that this algorithm, in addition to being very flexible, retains all the desirable features of these algorithms and is highly competitive to them in compression efficiency.

Hyperspectral Image Compression Using Three-Dimensional Wavelet Coding: A Lossy-to-Lossless Solution †

Abstract: We propose an embedded, block-based, image wavelet transform coding algorithm of low complexity. The embedded coding of Set Partitioned Embedded bloCK (SPECK) algorithm is modified and extended to three dimensions. The resultant algorithm, three-Dimensional Set Partitioned Embedded bloCK (3D-SPECK), efficiently encodes 3D volumetric image data by exploiting the dependencies in all dimensions. 3D-SPECK generates embedded bit stream and therefore provides progressive transmission. We describe the use of this coding algorithm in two implementations, including integer wavelet transform as well as floating point wavelet transform, where the former one enables lossy and lossless decompression from the same bit stream, and the latter one achieves better performance in lossy compression. Wavelet packet structure and coefficient scaling are used to make the integer filter transform approximately unitary. The structure of hyperspectral images reveals spectral responses that would seem ideal candidate for compression by 3D-SPECK. We demonstrate that 3D-SPECK, a wavelet domain compression algorithm, can preserve spectral profiles well. Compared with the lossless version of the benchmark JPEG2000 (multi-component), the 3D-SPECK lossless algorithm produces average of 3.0% decrease in compressed file size for Airborne Visible Infrared Imaging Spectrometer images, the typical hyperspectral imagery. We also conduct comparisons of the lossy implementation with other the state-of-the-art algorithms such as three-Dimensional Set Partitioning In Hierarchical Trees (3D-SPIHT) and JPEG2000. We conclude that this algorithm, in addition to being very flexible, retains all the desirable features of these algorithms and is highly competitive to 3D-SPIHT and better than JPEG2000 in compression efficiency.

A wavelet-based two-stage near-lossless coder

Abstract: In this paper, we investigate a two-stage near-lossless compression scheme. It is in the spirit of "lossy plus residual coding" and consists of a wavelet-based lossy layer followed by an arithmetic coding of the quantized residual to guarantee a given L/sup /spl infin// error bound in the pixel domain. Our focus is on the selection of the optimum bit rate for the lossy layer to achieve the minimum total bit rate. Unlike other similar lossy plus lossless approaches using a wavelet-based lossy layer, the proposed method does not require iteration of decoding and the IWT(Inverse Wavelet Transform) to locate the optimum bit rate. We propose a simple method to estimate the optimal bit rate and provide a theoretical justification for it. It is based on the 'critical rate' argument from the Rate-Distortion theory and 'whiteness' of the residual.

Lossy-to-lossless block-based compression of hyperspectral volumetric data

Abstract: An embedded, block-based, wavelet transform coding algorithm of low complexity is proposed. Three-dimensional set partitioned embedded block (3D-SPECK) efficiently encodes, hyperspectral volumetric image data by exploiting the dependencies in all dimensions. Integer wavelet transform is applied to enable lossy and lossless decompression from the same bit stream. We demonstrate that 3D-SPECK, a wavelet domain algorithm, like other time domain algorithms, can preserve spectral profiles well. Airborne visible infrared imaging spectrometer (AVIRIS) imagery is used to test the proposed algorithm. Results show that 3D-SPECK, in addition to being very flexible, retains all the desirable features of compared state-of-the-art algorithms and is highly competitive to 3D-SPIHT and better than JPEG2000 multi-component in compression efficiency.

Lossless Compression of Volumetric Medical Images with Improved Three-Dimensional SPIHT Algorithm

Abstract: This article presents a lossless compression of volumetric medical images with the improved three-dimensional (3-D) set partitioning in hierarchical tree (SPIHT) algorithm that searches on asymmetric trees. The tree structure links wavelet coefficients produced by 3-D reversible integer wavelet transforms. Experiments show that the lossless compression with the improved 3-D SPIHT gives improvement about 42% on average over two-dimensional techniques and is superior to those of prior results of 3-D techniques. In addition, we can easily apply different numbers of decomposition between the transaxial and axial dimensions, which is a desirable function when the coding unit of a group of slices is limited in size.

Kernel Fisher discriminant for steganalysis of JPEG hiding methods

Abstract: The use of kernel Fisher discriminants is used to detect the presence of JPEG based hiding methods. The feature vector for the kernel discriminant is constructed from the quantized DCT coefficient indices. Using methods developed in kernel theory a classifier is trained in a high dimensional feature space which is capable of discriminating original from stegoimages. The algorithm is tested on the F5 hiding method.

Fast additive noise steganalysis

Abstract: This work reduces the computational requirements of the additive noise steganalysis presented by Harmsen and Pearlman. The additive noise model assumes that the stegoimage is created by adding a pseudo-noise to a coverimage. This addition predictably alters the joint histogram of the image. In color images it has been shown that this alteration can be detected using a three-dimensional Fast Fourier Transform (FFT) of the histogram. As the computation of this transform is typically very intensive, a method to reduce the required processing is desirable. By considering the histogram between pairs of channels in RGB images, three separate two-dimensional FFTs are used in place of the original three-dimensional FFT. This method is shown to offer computational savings of approximately two orders of magnitude while only slightly decreasing classification accuracy.

Optimal error protection for real-time image and video transmission

Abstract: In this letter, a novel and computationally inexpensive analytic mean square error (mse) distortion rate (D-R) estimator for SPIHT which generates a nearly exact D-R function for the two- and three-dimensional SPIHT algorithm is presented. Utilizing our D-R estimate, we employ unequal error protection and equal error protection in order to minimize the end to end MSE distortion of the transform domain. A major contribution of this letter is the simple and extremely accurate analytical D-R model which potentially improves upon pre-existing methodologies and applications that rely on an accurate and computationally inexpensive D-R estimate.

Optimal error protection for real time image and video transmission

Abstract: In this paper a novel and computationally inexpensive analytic mean square error (MSE) distortion rate (D-R) estimator for SPIHT which generates a nearly exact distortion rate (D-R) function for the 2D and 3D SPIHT algorithm is presented. The analytical formula is derived from the observations that for any bit-plane coder, the slope of the D-R curve is constant for each level of the bit plane. Furthermore the slope of D-R curve reduces by a factor proportional to the level of the bit plane. An application of the derived results is presented in the area of 2D SPIHT transmission employing a binary symmetric channel (BSC) and Reed Solomon (RS) forward error correction (FEC) codes. Utilizing our D-R estimate, we employ unequal error protection (UEP) and equal error protection (EEP) in order to minimize the end to end mean square error (MSE) distortion of the transform domain. UEP yields a significant performance gain relative to EEP only when the average number of parity bits for a group of packets is constrained. When both the source rate and channel code rate varied under a bit budget constraint, optimal UEP yields only a slight improvement over the optimal EEP. A major contribution of this paper is the simple and extremely accurate analytical D-R model which potentially improves upon pre-existing methodologies and applications that rely on an accurate and computationally inexpensive D-R estimate. Another important contribution is that the optimum EEP, which requires almost no header information and can easily be computed using our method, is only slightly worse than the optimum UEP.

Robust image transmission using a new joint source channel coding algorithm and dual adaptive OFDM

Abstract: In this paper we consider the problem of robust image coding and packetization for the purpose of communications over slow fading frequency selective channels and channels with a shaped spectrum like those of digital subscribe lines (DSL). Towards this end, a novel and analytically based joint source channel coding (JSCC) algorithm to assign unequal error protection is presented. Under a block budget constraint, the image bitstream is de-multiplexed into two classes with different error responses. The algorithm assigns unequal error protection (UEP) in a way to minimize the expected mean square error (MSE) at the receiver while minimizing the probability of catastrophic failure. In order to minimize the expected mean square error at the receiver, the algorithm assigns unequal protection to the value bit class (VBC) stream. In order to minimizes the probability of catastrophic error which is a characteristic of progressive image coders, the algorithm assigns more protection to the location bit class (LBC) stream than the VBC stream. Besides having the advantage of being analytical and also numerically solvable, the algorithm is based on a new formula developed to estimate the distortion rate (D-R) curve for the VBC portion of SPIHT. The major advantage of our technique is that the worst case instantaneous minimum peak signal to noise ratio (PSNR) does not differ greatly from the averge MSE while this is not the case for the optimal single stream (UEP) system. Although both average PSNR of our method and the optimal single stream UEP are about the same, our scheme does not suffer erratic behavior because we have made the probability of catastrophic error arbitarily small. The coded image is sent via orthogonal frequency division multiplexing (OFDM) which is a known and increasing popular modulation scheme to combat ISI (Inter Symbol Interference) and impulsive noise. Using dual adaptive energy OFDM, we use the minimum energy necessary to send each bit stream at a particular probability of bit error. An added benefit of OFDM over serial transmission schemes is that some degree of progressiveness of SPIHT is preserved by transmitting both the VBC and LBC streams in parallel.

Near-lossless compression of digital terrain elevation data

Abstract: In critical applications of image compression that are sensitive to information loss, lossless compression techniques are usually employed. The compression ratios obtained from lossless techniques are low. Hence we need different schemes that give quantitative guarantees about the type and amount of distortion incurred, viz. near-lossless compression methods. In this paper, we explore hybrid techniques for near-lossless image compression based on error bound per pixel and apply them to Digital Terrain Elevation Data (DTED). We develop multi-stage quantization methods and other hybrid schemes using SPIHT as an embedded lossy coder. The methods developed are scalable with a control on maximum allowable deviation per pixel in the reconstruction. We compare the results obtained by these methods with JPEG-LS, the standard for lossless and near-lossless compression. Results show that these methods usually perform better than JPEG-LS in terms of compression performance and have additional features useful for progressive transmission.

Lossless compression for three-dimensional images

Abstract: We investigate and compare the performance of several three-dimensional (3D) embedded wavelet algorithms on lossless 3D image compression. The algorithms are Asymmetric Tree Three-Dimensional Set Partitioning In Hierarchical Trees (AT-3DSPIHT), Three-Dimensional Set Partitioned Embedded bloCK (3D-SPECK), Three-Dimensional Context-Based Embedded Zerotrees of Wavelet coefficients (3D-CB-EZW), and JPEG2000 Part II for multi-component images. Two kinds of images are investigated in our study -- 8-bit CT and MR medical images and 16-bit AVIRIS hyperspectral images. First, the performances by using different size of coding units are compared. It shows that increasing the size of coding unit improves the performance somewhat. Second, the performances by using different integer wavelet transforms are compared for AT-3DSPIHT, 3D-SPECK and 3D-CB-EZW. None of the considered filters always performs the best for all data sets and algorithms. At last, we compare the different lossless compression algorithms by applying integer wavelet transform on the entire image volumes. For 8-bit medical image volumes, AT-3DSPIHT performs the best almost all the time, achieving average of 12% decreases in file size compared with JPEG2000 multi-component, the second performer. For 16-bit hyperspectral images, AT-3DSPIHT always performs the best, yielding average 5.8% and 8.9% decreases in file size compared with 3D-SPECK and JPEG2000 multi-component, respectively. Two 2D compression algorithms, JPEG2000 and UNIX zip, are also included for reference, and all 3D algorithms perform much better than 2D algorithms.

Efficient image coding for access to pixel ranges

Abstract: Technical imaging applications such as coding "images" of digital elevation maps, require extracting regions of compressed images with the pixel values within a pre-defined range, without having to decompress the whole image. Previously, we introduced a class of nonlinear transforms which are small modifications of linear transforms to facilitate a search for the regions with pixel values below (above) a given 'threshold', without incurring any penalty in coding efficiency. However, coding efficiency had to be somewhat compromised when searching for regions with a given pixel 'range', especially at high coding rates. In this paper, we propose an improved method of pixel 'range' coding to deal with the aforementioned problem. Results show significant improvements in coding efficiency.

Block-based embedded color image and video coding

Abstract: Set Partitioned Embedded bloCK coder (SPECK) has been found to perform comparable to the best-known still grayscale image coders like EZW, SPIHT, JPEG2000 etc. In this paper, we first propose Color-SPECK (CSPECK), a natural extension of SPECK to handle color still images in the YUV 4:2:0 format. Extensions to other YUV formats are also possible. PSNR results indicate that CSPECK is among the best known color coders while the perceptual quality of reconstruction is superior than SPIHT and JPEG2000. We then propose a moving picture based coding system called Motion-SPECK with CSPECK as the core algorithm in an intra-based setting. Specifically, we demonstrate two modes of operation of Motion-SPECK, namely the constant-rate mode where every frame is coded at the same bit-rate and the constant-distortion mode, where we ensure the same quality for each frame. Results on well-known CIF sequences indicate that Motion-SPECK performs comparable to Motion-JPEG2000 while the visual quality of the sequence is in general superior. Both CSPECK and Motion-SPECK automatically inherit all the desirable features of SPECK such as embeddedness, low computational complexity, highly efficient performance, fast decoding and low dynamic memory requirements. The intended applications of Motion-SPECK would be high-end and emerging video applications such as High Quality Digital Video Recording System, Internet Video, Medical Imaging etc.