Blocking effect reduction of compressed images using classification-based constrained optimization

In this paper we propose an adaptive image restoration algorithm using block-based edge-classification for reducing block artifacts in compressed images. In order to efficiently reduce block artifacts, edge direction of each block is classified by using model-fitting criterion, and the constrained least-squares (CLS) filter with corresponding direction is used for restoring the block. The proposed restoration filter is derived based on the observation that the quantization operation in a series of coding processes is a nonlinear and many-to-one mapping operator. Then we propose an approximated version of a constrained optimization technique as a restoration process for removing the nonlinear and space-varying degradation operator. For real-time implementation, the proposed restoration filter can be realized in the form of a truncated FIR filter, which is suitable for postprocessing reconstructed images in digital TV, video conferencing systems, etc.     

Recompression of JPEG images by requantization

We report a novel heuristic for requantizing JPEG images. The resulting images are generally smaller and often have improved perceptual image quality over a "blind" requantization approach, that is, one that does not consider the properties of the quantization matrices. The heuristic is supported by a detailed mathematical treatment which incorporates the well-known Laplacian distribution of the AC discrete cosine transform (DCT) coefficients with an analysis of the error introduced by requantization. We note that the technique is applicable to any image compression method which employs discrete cosine transforms and quantization.     

JPEG2000对PMP图像压缩效果的定量研究

探讨了新一代静态图像压缩标准JPEG2000在三维面形测量中的应用.针对三维面形测量中的相位测量轮廓术,在减少图像存储空间,同时又不明显降低图像应用质量的前提下,采用了JPEG2000有损压缩技术对光栅投影图进行压缩.对相移法中得到的变形光栅图进行不同压缩比的压缩,比较了压缩后重构图像展开的相位与未经压缩的原图展开的相位之间的误差.通过定量计算压缩前后相位函数间的最大误差和均方根误差,分析了在相同压缩比的条件下,三维面形复杂程度与三维重建误差的关系.文中还比较了不同相移次数的光栅投影图的压缩对相位误差的影响.本文的研究结果对在相位测量轮廓术中合理的选择JPEG2000图像压缩比具有参考价值.     

Artifact reduction in JPEG2000 compressed images at low bit-rate using mathematical morphology filtering

JPEG2000 is known as an efficient standard to encode images. However, at very low bit-rates, artifacts or distortions can be observed in decoded images. In order to improve the visual quality of decoded images and make them perceptually acceptable, we propose in this work a new preprocessing scheme. This scheme consists in preprocessing the image to be encoded using a nonlinear filtering, considered as a prior phase to JPEG 2000 compression. More specifically, the input image is decomposed into low- and high-frequency sub-images using morphological filtering. Afterward, each sub-image is compressed using JPEG2000, by assigning different bit-rates to each sub-image. To evaluate the quality of the reconstructed image, two different metrics have been used, namely (a) peak signal to noise ratio, to evaluate the visual quality of the low-frequency sub-image, and (b) structural similarity index measure, to evaluate the visual quality of the high-frequency sub-image. Based on the reconstructed images, experimental results show that, at low bit-rates, the proposed scheme provides better visual quality compared to a direct use of JPEG2000 (excluding any preprocessing).     

低码率视频压缩技术的块效应消除方法

低友率视频压缩技术是多媒体通信的关键技术。基于块编码的低码率视频压缩技术中,块效应现象成为比较突出的问题。本文讨论了低码率视频压缩中消除块效应的方法,提出了基于约束复原原理的一种具体块效应消除方法,并根据计算机软件实现的分析,得出了结论采用约束复原的块应消除方法可以同时提高客观ＰＳＮＲ值和改善块应现象。     

JPEG compression history estimation for color images

We routinely encounter digital color images that were previously compressed using the Joint Photographic Experts Group (JPEG) standard. En route to the image's current representation, the previous JPEG compression's various settings-termed its JPEG compression history (CH)-are often discarded after the JPEG decompression step. Given a JPEG-decompressed color image, this paper aims to estimate its lost JPEG CH. We observe that the previous JPEG compression's quantization step introduces a lattice structure in the discrete cosine transform (DCT) domain. This paper proposes two approaches that exploit this structure to solve the JPEG Compression History Estimation (CHEst) problem. First, we design a statistical dictionary-based CHEst algorithm that tests the various CHs in a dictionary and selects the maximum a posteriori estimate. Second, for cases where the DCT coefficients closely conform to a 3-D parallelepiped lattice, we design a blind lattice-based CHEst algorithm. The blind algorithm exploits the fact that the JPEG CH is encoded in the nearly orthogonal bases for the 3-D lattice and employs novel lattice algorithms and recent results on nearly orthogonal lattice bases to estimate the CH. Both algorithms provide robust JPEG CHEst performance in practice. Simulations demonstrate that JPEG CHEst can be useful in JPEG recompression; the estimated CH allows us to recompress a JPEG-decompressed image with minimal distortion (large signal-to-noise-ratio) and simultaneously achieve a small file-size.     

Adjustable compression method for still JPEG images

There are a large number of image processing applications that work with different performance requirements and available resources. Recent advances in image compression focus on reducing image size and processing time, but offer no real-time solutions for providing time/quality flexibility of the resulting image, such as using them to transmit the image contents of web pages. In this paper we propose a method for encoding still images based on the JPEG standard that allows the compression/decompression time cost and image quality to be adjusted to the needs of each application and to the bandwidth conditions of the network. The real-time control is based on a collection of adjustable parameters relating both to aspects of implementation and to the hardware with which the algorithm is processed. The proposed encoding system is evaluated in terms of compression ratio, processing delay and quality of the compressed image when compared with the standard method.     

一种针对JPEG图像的通用隐写分析算法

提出了一种针对JPEG图像的通用隐写分析算法。该算法提取了15个具有良好分类特性的特征参数,输入构建的KS—SVM分类器．以达到检测载密图像的目的。实验结果表明,该算法的检测正确率较高,检测速度快,能够实现针对各类JPEG载密图像的有效检测。     

Multifidelity JPEG based compression of images using variablequantisation

In image processing applications, certain regions in an image may be of greater interest to the user. For these types of applications, a multifidelity region based variable quantisation scheme is proposed. The resulting subjective visual duality is considerably higher than for comparable compression ratios employing the standard JPEG implementation     

Joint trellis-coded quantization watermarking for JPEG2000 images

Watermarking in the Joint Photographic Experts Group (JPEG)2000 coding pipeline is investigated in this paper. A joint quantization and watermarking method based on trellis-coded quantization (TCQ) is proposed to reliably embed data during the quantization stage of the JPEG2000 part 2 codec. The central contribution of this work is the use of a single quantization module to jointly perform quantization and watermark embedding at the same time. The TCQ-based watermarking technique allows embedding the watermark in the detail sub-bands of one or more resolution levels except the first one. Watermark recovery is performed after image decompression. The performance of this joint scheme in terms of image quality and robustness against common image attacks was estimated on real images.     

Reconstruction of baseline JPEG coded images in error proneenvironments

A two-stage method for the reconstruction of missing data in the transmission of baseline JPEG coded images in error prone environments is proposed. In the first stage, we estimate the values of the missing DC coefficients. As effects of errors in estimating the missing DC values will appear as a number of stripes across the image, a technique for removing such stripes is also developed. In the second stage, the data of missing blocks is reconstructed by exploiting the correlation between adjacent blocks. Simulation results intricate that our reconstruction method performs very well. The two key contributions of our method are that it does not assume nondifferential encoding of the DC coefficients, and that it performs well in the reconstruction of diagonal edges.     

Classified JPEG coding of mixed document images for printing

This paper presents a modified JPEG coder that is applied to the compression of mixed documents (containing text, natural images, and graphics) for printing purposes. The modified JPEG coder proposed in this paper takes advantage of the distinct perceptually significant regions in these documents to achieve higher perceptual quality than the standard JPEG coder. The region-adaptivity is performed via classified thresholding being totally compliant with the baseline standard. A computationally efficient classification algorithm is presented, and the improved performance of the classified JPEG coder is verified.     

Digital fragile watermarking scheme for authentication of JPEG images

It is a common practice in transform-domain fragile watermarking schemes for authentication purposes to watermark some selected transform coefficients so as to minimise embedding distortion. The author points out that leaving most of the coefficients unmarked results in a wide-open security gap for attacks to be mounted on them. A fragile watermarking scheme is proposed to implicitly watermark all the coefficients by registering the zero-valued coefficients with a key-generated binary sequence to create the watermark and involving the unwatermarkable coefficients during the embedding process of the embeddable ones. Non-deterministic dependence is established by involving some of the unwatermarkable coefficients selected according to the watermark from a nine-neighbourhood system in order to thwart different attacks, such as cover-up, vector quantisation and transplantation. No hashing is needed in establishing the non-deterministic dependence.     

一种基于JPEG压缩图像的信息隐藏方法

描述了一种基于JPEG图像的信息隐藏新方法.该方法用I/I矩阵在8×8子块DCT域的2m比特中低频量化系数的最低位中,最多修改[m/2]比特数据,即可嵌入m比特信息,有较高的数据嵌入率及较好隐蔽性.该方法已在计算机上进行了模拟实验,并获得了较好的结果.     

Locating edges and removing ringing artifacts in JPEG images by frequency-domain analysis.

We present a method of locating edges in JPEG-coded images which operates in frequency space on the DCT coefficients. Applied to the quantized DCT coefficients of a block containing a straight edge, the method yields an equation for the edge in a fraction of the operations needed to dequantize and transform the coefficents to pixel values. As a sample application of this method, we present a technique for alleviating ringing artifacts in JPEG-coded images.     

Combined edge crispiness and statistical differencing fordeblocking JPEG compressed images

In this work, a new approach is proposed that deals with blocking effects in JPEG compressed images. High-frequency details of the coded images are mainly contaminated by quantization noise. Preserving the image details and reducing the effect of quantization noise as much as possible can improve the ability of any enhancing method. To achieve this goal along with the removal of the blocking effect, the high-frequency components of the image are first extracted by high pass filtering. The result is then scaled by a factor that depends on the compression ratio and subtracted from the observed image. This result is used to design an adaptive filter that depends on the statistical behavior of the preprocessed image. The adaptive filter is applied to the resultant image. The result shows high SNR, significant improvement in the separation between blocking noise and image features, and effective reduction of image blurring. Other steps are required to preserve the global and local edges of the processed image, remove blocking noise, and ensure smoothness without blurring. These steps are dedicated to remove blocking artifacts and to enhance feature regularities. The evaluation of this approach in comparison with other techniques is carried out both subjectively and qualitatively.     

Superresolution restoration of an image sequence: adaptivefiltering approach

This paper presents a new method based on adaptive filtering theory for superresolution restoration of continuous image sequences. The proposed methodology suggests least squares (LS) estimators which adapt in time, based on adaptive filters, least mean squares (LMS) or recursive least squares (RLS). The adaptation enables the treatment of linear space and time-variant blurring and arbitrary motion, both of them assumed known. The proposed new approach is shown to be of relatively low computational requirements. Simulations demonstrating the superresolution restoration algorithms are presented.     

Compressing the background layer in compound images,using JPEG and data filling

To efficiently compress rasterized compound documents, an encoder must be content-adaptive. Content adaptivity may be achieved by employing a layered approach. In such an approach, a compound image is segmented into layers so that appropriate encoders can be used to compress these layers individually. A major factor in using standard encoders efficiently is to match the layers’ characteristics to those of the encoders by using data filling techniques to fill-in the initially sparse layers. In this work we present a review of methods dealing with data filling and propose also a sub-optimal non-linear projections scheme that efficiently matches the baseline JPEG coder in compressing background layers, leading to smaller files with better image quality.     

Prefetching and caching strategies for remote and interactive browsing of JPEG2000 images.

This paper considers the issues of scheduling and caching JPEG2000 data in client/server interactive browsing applications, under memory and channel bandwidth constraints. It analyzes how the conveyed data have to be selected at the server and managed within the client cache so as to maximize the reactivity of the browsing application. Formally, to render the dynamic nature of the browsing session, we assume the existence of a reaction model that defines when the user launches a novel command as a function of the image quality displayed at the client. As a main outcome, our work demonstrates that, due to the latency inherent to client/server exchanges, a priori expectation about future navigation commands may help to improve the overall reactivity of the system. In our study, the browsing session is defined by the evolution of a rectangular window of interest (WoI) along the time. At any given time, the WoI defines the position and the resolution of the image data to display at the client. The expectation about future navigation commands is then formalized based on a stochastic navigation model, which defines the probability that a given WoI is requested next, knowing previous WoI requests. Based on that knowledge, several scheduling scenarios are considered. The first scenario is conventional and transmits all the data corresponding to the current WoI before prefetching the most promising data outside the current WoI. Alternative scenarios are then proposed to anticipate prefetching, by scheduling data expected to be requested in the future before all the current WoI data have been sent out. Our results demonstrate that, for predictable navigation commands, anticipated prefetching improves the overall reactivity of the system by up to 30% compared to the conventional scheduling approach. They also reveal that an accurate knowledge of the reaction model is not required to get these significant improvements.     

Fuzzy clustering for colour reduction in images

The aim of colour quantisation is to reduce the number of distinct colour in images while preserving a high colour fidelity as compared to the original images. The choice of a good colour palette is crucial as it directly determines the quality of the resulting image. Colour quantisation can also be seen as a clustering problem where the task is to identify those clusters that best represent the colours in an image. In this paper we investigate the performance of various fuzzy c-means clustering algorithms for colour quantisation of images. In particular, we use conventional fuzzy c-means as well as some more efficient variants thereof, namely fast fuzzy c-means with random sampling, fast generalised fuzzy c-means, and a recently introduced anisotropic mean shift based fuzzy c-means algorithm. Experimental results show that fuzzy c-means performs significantly better than other, purpose built colour quantisation algorithms, and also confirm that the fast fuzzy clustering algorithms provide similar quantisation results to the full conventional fuzzy c-means approach.