JPEG Lossy Research Articles

A new approach to high-capacity annotation watermarking based on digital fountain codes

Annotation watermarking is a technique that allows to associate content descriptions with digital images in a persistent and format independent manner. It is commonly used in medical applications and, hence, existing schemes have been designed to meet rigorous watermark transparency requirements. As a result, the effective capacity of such schemes is severely limited. In this paper, we present a new approach to annotation watermarking. We adopt the fountain coding paradigm and design a convenient watermark communication architecture which resembles a traditional packet network. Our approach allows for straightforward incorporation of content adaptivity, robustness against cropping and support for multiple data streams. In our study, we focus on high-capacity annotations and we assume different requirements with respect to the fidelity of the watermarked images. Our scheme is robust against lossy JPEG compression and cropping. This paper describes the principles of the proposed approach and presents the results of it’s experimental evaluation.

Dual Video Watermarking Scheme Based on Transform Domain

The single watermark algorithms always merely have single function. In order to overcome the drawback, this paper proposed a dual video watermarking scheme based on transform domain. To implement the video copyright and integrality authentication, this paper embedded robust watermarking and fragile watermark. At the same time, this scheme made good use of the wavelet transform to embed the two different kinds of watermarking in the same video respectively. The fragile watermarking is to serve the robust watermarking. Experiments demonstrate this scheme can not only protect the copyright of the video effectively, but also protect against some attacks, such as shearing attack, JPEG lossy compression attack, noise attack etc. This scheme has better robustness and invisibility.

Digital Image Watermarking Based on Mixed Error Correcting Code

In this paper, we present a novel technique based on a mixed Error Correcting Code(ECC)-the convolutional code and the repetition code to enhance the robustness of the embedded watermark. Before embedding, the binary watermark is scanned to one-dimension sequence and later inputted into the (3, 1, 2) convolutional encoder and (3, 1) repetition encoder frame by frame, which will improve the error correcting capability of decoder. The output code sequence is scanned to some matrixes as the new watermark messages. The watermarking is selected in low frequency band of the Discrete Wavelet Transform (DWT) and therefore it can resist the destruction of image processing. Experimental results are presented to demonstrate that the robustness of a watermark with mixed ECC is much higher than the traditional one just with repetition coding while suffering JPEG lossy compression, salt and pepper noise and center cutting processing.

Vpliv stiskanja jpeg2000 z izgubami na klasifikacijo posnetkov worldview-2

Vpliv stiskanja jpeg2000 z izgubami na klasifikacijo posnetkov worldview-2

Embedding color watermarks in color images based on Schur decomposition

In this paper, a blind dual color image watermarking scheme based on Schur decomposition is introduced. This is the first time to use Schur decomposition to embed color image watermark in color host image, which is different from using the binary image as watermark. By analyzing the 4×4 unitary matrix U via Schur decomposition, we can find that there is a strong correlation between the second row first column element and the third row first column element. This property can be explored for embedding watermark and extracting watermark in the blind manner. Since Schur decomposition is an intermediate step in SVD decomposition, the proposed method requires less number of computations. Experimental results show that the proposed scheme is robust against most common attacks including JPEG lossy compression, JPEG 2000 compression, low-pass filtering, cropping, noise addition, blurring, rotation, scaling and sharpening et al. Moreover, the proposed algorithm outperforms the closely related SVD-based algorithm and the spatial-domain algorithm.

SemiFragile Watermarking Scheme based on Feature in Dwt Domain

In DWT domain, A novel semi-fragile watermarking is the scheme for the purpose of authenticating the image and also tamper localization. In this scheme, to generate the watermark, we extract the content-based image features in the wavelet domain in particular from the approximation subband. Later, we embed the watermark into the middle subband. Then, the main goals of this scheme i.e., image authentication and tamper localization are achieved by comparing the matrices of extracted content based image with the extracted watermark. It is proven that this proposed scheme is very robust for common content preserving image processing like noise-adding and lossy JPEG compression through experimental results. The impact of this scheme to malicious tamper in images is fragile. The proposed scheme is very accurate in detecting the tamper location.

Fractal Analysis of Periapical Bone from Lossy Compressed Radiographs: A Comparison of Two Lossy Compression Methods

The aim of the study was to evaluate the effect of two lossy image compression methods on fractal dimension (FD) calculation. Ten periapical images of the posterior teeth with no restorations or previous root canal therapy were obtained using storage phosphor plates and were saved in TIF format. Then, all images were compressed with lossy JPEG and JPEG2000 compression methods at five compression levels, i.e., 90, 70, 50, 30, and 10. Compressed file sizes from all images and compression ratios were calculated. On each image, two regions of interest (ROIs) containing healthy trabecular bone in the posterior periapical area were selected. The FD of each ROI on the original and compressed images was calculated using differential box counting method. Both image compression and analysis were performed by a public domain software. Altogether, the FD of 220 ROIs was calculated. FDs were compared using ANOVA and Dunnett tests. The FD decreased gradually with compression level. A statistically significant decrease of the FD values was found for JPEG 10, JPEG2000 10, and JPEG2000 30 compression levels (p < 0.05). At comparable file sizes, the JPEG induced a smaller FD difference. In conclusion, lossy compressed images with appropriate compression level may be used for FD calculation.

Blind-restoration-based blind separation method for permuted motion blurred images

A novel single-channel blind separation algorithm for permuted motion blurred images is proposed by using blind restoration in this paper. Both the motion direction and the length of the point spread function (PSF) are estimated by Radon transformation and extrema a detection. Using the estimated blur parameters, the permuted image is restored by performing the L-R blind restoration method. The permutation mixing matrices can be accurately estimated by classifying the ringing effect in the restored image, thereby the source images can be separated. Simulation results show a better separation efficiency for the permuted motion blurred image with various permutation operations. The proposed algorithm indicates a better performance on the robustness against Gaussian noise and lossy JPEG compression.

Integer Computation of Lossy JPEG2000 Compression

In this paper, an integer-based Cohen-Daubechies-Feauvea (CDF) 9/7 wavelet transform as well as an integer quantization method used in a lossy JPEG2000 compression engine is presented. The conjunction of both an integer transform and quantization step allows for a complete integer computation of lossy JPEG2000 compression. The lossy method of compression utilizes the CDF 9/7 wavelet filter, which transforms integer input pixel values into floating-point wavelet coefficients that are then quantized back into integers and finally compressed by the embedded block coding with optimal truncation tier-1 encoder. Integer computation of JPEG2000 allows a reduction in computational complexity of the wavelet transform as well as ease of implementation in embedded systems for higher computational performance. The results of the integer computation show an equivalent rate/distortion curve to the JasPer JPEG2000 compression engine, as well as a 30% reduction in computation time of the wavelet transform and a 56% reduction in computation time of the quantization processing on an average.

CRT 기반의 DCT 영역 제로-워터마킹

Zero-watermarking is a digital watermarking technique that can escape from data distortion and quality degradation by no watermark insertion into digital images to be watermarked. This paper proposes DCT0CRT, a CRT-based zero-watermarking technique in the domain of DCT. One of the DC and low-frequency AC coefficients of each DCT block chosen in chaotic way from an image is selected by testing whether it satisfies the CRT-based condition matching with the watermark bit to be embedded. Such selection information forms a key to extract the watermark from the watermarked image. Experimental results show that the image quality watermarked by DCT0CRT is better than that watermarked by any other CRT-based watermarking techniques and the inserted watermark is robust against some common attacks such as sharpening, blurring, and JPEG lossy compression.

Investigating the relationship between image enhancement and image compression in the context of the multi-scale retinex

Image enhancement and data compression methods arose from the distinct and largely separate disciplines of image processing and communications respectively, yet both are important components of current and future digital imaging systems technology. Here we examine the relationship of these two components with special emphasis on image enhancement and lossy jpeg image compression. When transmission channel capacity is limited, image/data compression is often performed to increase the data throughput. However, this compression has a significant impact on the quality of the final data that is received. In most cases, image enhancement performed after image compression tends to bring out the artifacts injected into the data due to the compression. However, if image enhancement is performed before image compression, there are two issues that arise: (i) image enhancement typically increases the contrast—amount of observable detail—in an image which leads to poorer compression ratios; and (ii) the radiometric information in the original data is typically irretrievably lost. In this paper we address the impact of image enhancement, specifically that of the multi-scale retinex with color restoration ( msrcr) on image compression, and vice versa. We also look at the impact of compression on recovering original data from enhanced imagery given certain parameters about the enhancement process. In this context, we also develop an inversion process for the msrcr.

An improved low complexity Near Lossless Image Compression

In this paper, a new improved low complexity compression methodology named as Near Lossless Image Compression (NLIC) has been suggested. This algorithm is a hybrid method which includes DCT, a lossy compression technique and JPEG encoding using entropy based Huffman coding, a lossless compression technique. The algorithm is tested with standard square images of sizes 512 × 512 and 1024 × 1024 respectively. The results of NLIC are also compared with the Huffman and Run length Encoding (RLE) for evaluating its compression efficiency.

Efficient block prediction-based coding of computer screen images with precise block classification

This study presents a precise, one-pass block classification algorithm for efficient coding of computer screen images like power-point presentations, webpages and wall papers. The objective is to minimise the loss of visual quality of text during compression by separating text information which needs high spatial resolution than the pictures and background. It segments computer screen images into text/graphic, picture/background blocks by computing the statistical feature based on discrete wavelet transforms coefficients in the detail sub-bands of each 8×8 block, and then compresses the text/graphics pixels losslessly with a two-mode block prediction coding and the background pixels with the lossy JPEG algorithm. The proposed scheme performs accurate block classification of text information with different fonts, sizes and ways of arrangement from the background image, so that text/graphics blocks are compressed at higher quality than background image blocks. Experimental results show that the proposed method minimises block classification error and improves the value of peak signal-to-noise ratio significantly than standard JPEG, JPEG-2000 and H.264/AVC-I, while keeping competitive compression ratio and visually lossless quality of text information.

THE EFFECTS OF COMPRESSION ON ULTRA WIDEBAND RADAR SIGNALS

Over the past ten years, Ultra Wideband (UWB) Radar has been widely investigated as a biomedical imaging modality, used to detect early-stage breast cancer and to continuously monitor vital signs using both wearable and contactless devices. The advantages of the technology in terms of low-power requirements and non-ionising radiation are well recognised, with the technology being applied to a range of non-invasive medical applications, from respiration to heart monitoring. Across all these applications, there is a strong necessity to e-ciently manage the large quantities of UWB data which will be captured. For wearable devices in particular, the e-cient compression of UWB data allows the monitoring system to conserve limited resources such as memory and battery capacity, by reducing data storage and in some cases transmission requirements. In contrast to lossless compression techniques, lossy compression algorithms can achieve higher compression ratios and consequently greater power savings, at the expense of a marginal degradation of the reconstructed signal. This paper compares the lossy JPEG2000 and Set Partitioning In Hierarchical Trees (SPIHT) algorithms for UWB signal compression. This study examines the efiects of lossy signal compression on an UWB breast cancer classiflcation algorithm. This particular application was chosen because the classiflcation algorithm relies heavily on shape and surface texture detail embedded in the Radar Target Signature (RTS) of the tumour, and therefore will provide both a robust and easily quantiflable test platform for the compression algorithms. The

Near-lossless and lossy compression of imaging spectrometer data: comparison of information extraction performance

We investigate the ability to derive meaningful information from decompressed imaging spectrometer data. Hyperspectral images are compressed with near-lossless and lossy coding methods. Linear prediction between the bands is used in both cases. Each band is predicted by a previously transmitted band. The residual is formed by subtracting the prediction from the original data and then is compressed either with a near-lossless bit-plane coder or with the lossy JPEG2000 algorithm. We study the effects of these two types of compression on hyperspectral image processing such as mineral and vegetation content classification using whole- and mixed pixel analysis techniques. The results presented in this paper indicate that an efficient lossy coder outperforms near-lossless method in terms of its impact on final hyperspectral data applications.

A novel zero-watermark copyright authentication scheme based on lifting wavelet and Harris corner detection

In this paper, a novel zero-watermark copyright authentication scheme based on Internet public certification system is proposed. This approach utilizes Haar integer wavelet transform based on a lifting scheme and adaptive Harris corner detection to extract image features, which will be used to produce a binary feature map, and the map is very crucial to the generation of watermark registered later. By properly choosing the parameters of aforementioned techniques such as the threshold T and the radius of local feature region R, the feature map is so much more stable and distinguishing that it can be used to construct robust watermark. Simulations demonstrate that the proposed scheme is resistant to many kinds of signal processing and malicious attacks such as Gaussian blurring, additive noising, JPEG lossy compression, cropping, scaling and slight rotation operation. Compared with a relative scheme such as that of Chang’s, the scheme in this paper is more practicable and reliable and can be applied to the area of copyright protection.

Copyright protection scheme for still images based on an image pinned field

Watermark embedding processes usually result in some deg- radation of the digital multimedia contents. Hence, they are not suitable for valuable and sensitive digital multimedia contents. Therefore, schemes combining signature with digital watermarking-like techniques have been proposed. Based on the general model for these combined schemes, a new scheme for image copyright protection by utilizing the pinned field of the protected image is proposed in this paper. The pinned field explores the texture information of the images and can be used to enhance the watermark robustness. Experimental results show that the proposed scheme works well under different signal-processing and geo- metric transformation attacks. On the other hand, in comparison with related schemes in the literature, our proposed scheme also has better performance. Furthermore, the proposed scheme is robust to both JPEG lossy compression and additive Gaussian noise. © 2010 Society of Photo-

Exploring Duplicated Regions in Natural Images

Duplication of image regions is a common method for manipulating original images, using typical software like Adobe Photoshop, 3DS MAX, etc. In this study, we propose a duplication detection approach that can adopt two robust features based on discrete wavelet transform (DWT) and kernel principal component analysis (KPCA). Both schemes provide excellent representations of the image data for robust block matching. Multiresolution wavelet coefficients and KPCA-based projected vectors corresponding to image-blocks are arranged into a matrix for lexicographic sorting. Sorted blocks are used for making a list of similar point-pairs and for computing their offset frequencies. Duplicated regions are then segmented by an automatic technique that refines the list of corresponding point-pairs and eliminates the minimum offset-frequency threshold parameter in the usual detection method. A new technique that extends the basic algorithm for detecting Flip and Rotation types of forgeries is also proposed. This method uses global geometric transformation and the labeling technique to indentify the mentioned forgeries. Experiments with a good number of natural images show very promising results, when compared with the conventional PCA-based approach. A quantitative analysis indicate that the wavelet-based feature outperforms PCA- or KPCA-based features in terms of average precision and recall in the noiseless, or uncompressed domain, while KPCA-based feature obtains excellent performance in the additive noise and lossy JPEG compression environments.

Lossy JPEG Compression in Quantitative Angiography: the Role of X-ray Quantum Noise

In medical imaging, contrary to applications in the consumer market, the use of irreversible or lossy compression is still in its beginnings. This is due to the suspected risk of compromising the diagnostic content. Many studies have been performed, but it was not until 2008 that national activities in different countries resulted in recommendations for the safe use of irreversible image compression in clinical practice. Quantitative coronary angiography (QCA), however, poses a special problem, since here a large variation in published maximum compression factors has strengthened the general concerns about the use of lossy techniques. Up to now, the reason for the variation has not been thoroughly investigated. Reasons for the discrepancies in published compression factors are determined in this study. Since JPEG compression reduces the quantum noise of the X-ray images, the impact of compression is overestimated when interpreting any change in local diameter as an error. By taking into consideration the quantitative effect of quantum noise in QCA, it is shown that the influence of JPEG compression can be neglected for compression factors up to ten at clinically applicable X-ray doses. This limit is comparable to that found by visual analysis for aesthetic image quality. Future studies on image compression effects should take the interaction with quantum noise explicitly into consideration.

An Adaptive Data Hiding Technique for Digital Image Authentication

The proposed scheme combines the advantages of cryptographic concept and imperceptibility feature of digital image watermarking in spatial domain. The watermark is first generated based on one-way hash function with the help of user key. Each bit of this new generated watermark is then embedded into respective blocks of the original image, in raster scan order. The embedding is performed by modifying the average value of pixel intensity of each block within a range specified by the contrast value for a given block. This reduces the effects of the modification as perceived by the human eye. The extraction procedure computes and compares the sum of the pixels values for the blocks of the original and watermarked image. The results demonstrates the robustness of scheme against common image processing operations like cropping, modification, low pass filter, median pass filter, scaled down and lossy JPEG compression with various quality index factor. Results also illustrate that the watermark is secure, recoverable and recognizable even after the watermarked image has been tampered, forged and modified by common image processing operations. The comparative study of proposed scheme with existing scheme has also been performed to observe the strength of the scheme.