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.     

A gradient-based optimization approach for reduction of blocking artifacts in JPEG images

This paper presents a gradient-based optimization approach to achieve reduction of blocking artifacts in compressed JPEG images. This approach involves decomposing a JPEG image into 1-D signals once along the rows or columns and once along the columns or rows. The reduction of blocking artifacts is carried out per 1-D signal by an optimization formulation where the gradient of an original 1-D signal is approximated based on the gradient of a compressed signal. A fixed-weight and an adaptive-weight optimization formulation are considered and solved analytically. A restored image is reconstructed by aggregating recovered 1-D signals. The performance of the developed method is assessed by examining both gray-level and color images and by computing the three measures of PSNR, SSIM, and GBIM. Comparison results with five existing methods are also reported.     

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。     

基于局部块效应的JPEG伪造图像的盲取证

本文基于对JPEG图像整体块效应的分析,定义了新的针对图像局部区域的块效应评价,并由此提出了一种有效的JPEG伪造图像盲取证方法。首先获得图像在水平方向和垂直方向的差分图像,然后将两个方向的差分图像分别进行特定大小的分块,再计算每个分块局部区域的块效应评价,根据待测图像不同区域局部块效应评价的明显差异检测出图像被篡改的位置。实验结果表明,该方法可以有效的检测出经过JPEG双压缩的伪造图像。      

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.     

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.     

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     

Kurtosis-based no-reference quality assessment of JPEG2000 images

No-reference (NR) image quality assessment (QA) presumes no prior knowledge of reference (distortion-free) images and seeks to quantitatively predict visual quality solely from the distorted images. We develop kurtosis-based NR quality measures for JPEG2000 compressed images in this paper. The proposed measures are based on either 1-D or 2-D kurtosis in the discrete cosine transform (DCT) domain of general image blocks. Comprehensive testing demonstrates their good consistency with subjective quality scores as well as satisfactory performance in comparison with both the representative full-reference (FR) and state-of-the-art NR image quality measures.     

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.     

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.     

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.     

A requantization algorithm for the transcoding of JPEG images

Photos from digital camera are mostly lossy compressed in JPEG format, and almost all users do not save or cannot access the original image. Sometimes we need to reduce the size of this JPEG file for saving the disk space or for sending the image to the device with limited bandwidth and/or display size. Since the original image is not available, we need to recompress the already compressed photos. In the existing literature, it is revealed that the direct transcoding (decompressing the JPEG image and then compressing it again with a larger step size) generally results in lower quality images when compared to the one compressed from the original image with the same parameters. This discrepancy is due to the requantization error, and the existing algorithms for more efficient transcoding were focused on finding the requantization step sizes for reducing this error. In this paper, we propose an algorithm that manipulates the requantized DCT coefficients for enhancing the quality of transcoded image, regardless of the choice of requantization step sizes. For this purpose, we first locate the DCT coefficients which have the possibility of causing large requantization errors. But, since the exact requantization error cannot be computed without the original image, we define the error as the discontinuity of pixels around the block boundaries, between the given JPEG image and the targeting one. Then, for the possible variants of these coefficients, the errors are computed and the best combination of coefficients is found. Experimental results show that more coefficients are correctly quantized than the conventional direct requantization, and thus the PSNR as well as the subjective quality is much improved.     

CNN-based first quantization estimation of double compressed JPEG images

Multiple JPEG compressions leave artifacts in digital images: residual traces that could be exploited in forensics investigations to recover information about the device employed for acquisition or image editing software. In this paper, a novel First Quantization Estimation (FQE) algorithm based on convolutional neural networks (CNNs) is proposed. In particular, a solution based on an ensemble of CNNs was developed in conjunction with specific regularization strategies exploiting assumptions about neighboring element values of the quantization matrix to be inferred. Mostly designed to work in the aligned case, the solution was tested in challenging scenarios involving different input patch sizes, quantization matrices (both standard and custom) and datasets (i.e., RAISE and UCID collections). Comparisons with state-of-the-art solutions confirmed the effectiveness of the presented solution demonstrating for the first time to cover the widest combinations of parameters of double JPEG compressions.     

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.     

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.