Reduction of blocking effect in DCT-coded images based on a visual perception criterion

Blocking effect constitutes one of the main drawbacks of the actual DCT-based compression methods. We propose in this paper a new block reduction technique; it is based on a space-variant non-linear filtering operation of the blocking artifacts present in the image to be reconstructed. To account for the perceptual importance of the distortion, the amount of smoothing is adapted to the visibility of the blocking effect. A visibility parameter is computed for each artifact using the psychovisual properties of the human visual system (HVS). The postprocessing algorithm is in conformity with actual existing compression standards; it provides a way to greatly reduce the artifacts without degrading high-frequency information of the original image. First the proposed method is described and then experimental results are presented, showing the effectiveness of the correction.     

New simple and efficient color space transformations for lossless image compression

We present simple color space transformations for lossless image compression and compare them with established transformations including RCT, YCoCg-R and with the optimal KLT for 3 sets of test images and for significantly different compression algorithms: JPEG-LS, JPEG2000 and JPEG XR. One of the transformations, RDgDb, which requires just 2 integer subtractions per image pixel, on average results in the best ratios for JPEG2000 and JPEG XR, while for a specific set or in case of JPEG-LS its compression ratios are either the best or within 0.1 bpp from the best. The overall best ratios were obtained with JPEG-LS and the modular-arithmetic variant of RDgDb (mRDgDb). Another transformation (LDgEb), based on analog transformations in human vision system, is with respect to complexity and average ratios better than RCT and YCoCg-R, although worse than RDgDb; for one of the sets it obtains the best ratios.     

基于正则化方向失真的压缩图像质量评价

图像质量评价是图像和视频处理系统中的基本算法。该文在分析人眼视觉系统对图像感知特点的基础上,结合二维图像的几何本征特征研究,提出了一种新型的基于图像正则化方向失真的完全参考质量评价算法。该方法计算简单,物理意义明确。仿真试验结果表明,该方法符合人眼视觉系统特性,所得到的图像质量客观评价结果与主观评价结果之间具有更好的一致性。     

A weighted full-reference image quality assessment based on visual saliency

In full reference image quality assessment (IQA), the images without distortion are usually employed as reference, while the structures in both reference images and distorted images are ignored and all pixels are equally treated. In addition, the role of human visual system (HVS) is not taken account into subjective IQA metric. In this paper, a weighted full-reference image quality metric is proposed, where a weight imposed on each pixel indicates its importance in IQA. Furthermore, the weights can be estimated via visual saliency computation, which can approximate the subjective IQA via exploiting the HVS. In the experiments, the proposed metric is compared with several objective IQA metrics on LIVE release 2 and TID 2008 database. The results demonstrate that SROCC and PLCC of the proposed metric are 0.9647 and 0.9721, respectively,which are higher than other methods and it only takes 427.5 s, which is lower than that of most other methods.     

视觉信号质量评价的挑战与新进展

While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal processing and communication algorithms, as well as various related decision-making processes. In this pa-per, we first provide an overview of recently derived quality assessment approaches for traditional visual signals (i.e., 2D im-ages/videos), with highlights for new trends (such as machine learning approaches). On the other hand, with the ongoing development of devices and multimedia services, newly emerged visual signals (e.g., mobile/3D videos) are becoming more and more popular. This work focuses on recent progresses of quality metrics, which have been reviewed for the newly emerged forms of visual signals, which include scalable and mobile videos, High Dynamic Range (HDR) images, image segmentation results, 3D images/videos, and retargeted images.     

A novel method for lossless image compression and encryption based on LWT,SPIHT and cellular automata

In this paper, a novel method for lossless image encryption based on set partitioning in hierarchical trees and cellular automata. The proposed encryption method embeds the encryption into the compression process, in which a small part of the data is encrypted quickly, while maintaining the good coding characteristics of set partitioning in hierarchical trees (SPIHT). The proposed encryption system adopts three stages of scrambling and diffusion. In each stage of encryption, different chaotic systems are used to generate the plaintext-related key stream to maintain high security and to resist some attacks. Moreover, the channel length of the coded-and-compressed color image is more uncertain, resulting into higher difficulty for attackers to decipher the algorithm. The experimental results indicate that the length of bitstream is compressed to 50% of the original image, showing that our proposed algorithm has higher lossless compression ratio compared with the existing algorithms. Meanwhile, the encryption scheme passes the entropy analysis, sensitivity analysis, lossless recovery test, and SP800-22 test.     

Perceptual Quality Assessment of SAR Image Compression Based on Image Content Partition and Neural Network

Image quality assessment （IQA） is of fundamental importance for image compression applications. Traditional IQA measures used for Synthetic aperture radar （SAR） image compression do not consider the properties of Human visual system （HVS）. Since human beings are the final users in most SAR image applications, the objective evaluation coordinate to human＇s perception is the most acceptable and practical IQA method. In this paper, we propose a novel objective approach based on image content partition and Neural network （NN） by introducing the HVS and SAR image characteristics. Experimental results demonstrate that the proposed metric correlates well with subjective quality of SAR image compression and outperforms those state-of-art objective models using Structural similarity index （SSIM）, Singular value decomposition （SVD） and Visual information fidelity （VIF）.     

A survey of perceptual image processing methods

Perceptual approaches have been widely used in many areas of visual information processing. This paper presents an overview of perceptual based approaches for image enhancement, segmentation and coding. The paper also provides a brief review of image quality assessment (IQA) methods, which are used to evaluate the performance of visual information processing techniques. The intent of this paper is not to review all the relevant works that have appeared in the literature, but rather to focus on few topics that have been extensively researched and developed over the past few decades. The goal is to present a perspective as broad as possible on this actively evolving domain due to relevant advances in vision research and signal processing. Therefore, for each topic, we identify the main contributions of perceptual approaches and their limitations, and outline how perceptual vision has influenced current state-of-the-art techniques in image enhancement, segmentation, coding and visual information quality assessment.     

Visual-PSNR measure of image quality

Objective assessment of image quality is important in numerous image and video processing applications. Many objective measures of image quality have been developed for this purpose, of which peak signal-to-noise ratio PSNR is one of the simplest and commonly used. However, it sometimes does not match well with objective mean opinion scores (MOS). This paper presents a novel objective full-reference measure of image quality (VPSNR), which is a modified PSNR measure. It will be shown that VPSNR takes into account some features of the human visual system (HVS). The performance of VPSNR is validated using a data set of four image databases, and in this article it is shown that for images compressed by block-based compression algorithms (like JPEG) the proposed measure in the pixel domain matches well with MOS.     

MPEG-2标准的码率控制算法

在ＴＭ５算法的基础上，提出了一种ＭＰＥＧ－２码率控制算法。仿真实验表明，算法对有场景切换连续序列解码后的图象主客观质量有明显改善。     

计算机X光影像仪图像采集卡的设备驱动程序

简述了计算机X光影像仪（CR）的特点，介绍了CR系统中X光图像的数字化方法，给出数字化的X光图像数据采集的硬件电路。简要说明了WindowsNT及其核心模式驱动程序的结构，阐释了在WindowsNT下I／O请求的工作原理。利用NT DDK开发出计算机X光影像仪图像采集卡的核心模式设备驱动程度，通过软，硬件相结合的方法实现了对X光图像数据的实时采集和存储，经长时间的实验证明该方法可行，可靠，完全满足技术指标要求。     

计算机X光影像仪图像采集卡的设备驱动程序

简述了计算机X光影像仪(CR)的特点,介绍了CR系统中X光图像的数字化方法,给出数字化后的X光图像数据采集的硬件电路.简要说明了Windows NT及其核心模式驱动程序的结构,阐释了在Windows NT下I/O请求的工作原理.利用NT DDK开发出计算机X光影像仪图像采集卡的核心模式设备驱动程序,通过软、硬件相结合的方法实现了对X光图像数据的实时采集和存储,经长时间的实验证明该方法可行、可靠,完全满足技术指标要求.     

Visibility of quantization errors in reversible JPEG2000

Image compression systems that exploit the properties of the human visual system have been studied extensively over the past few decades. For the JPEG2000 image compression standard, all previous methods that aim to optimize perceptual quality have considered the irreversible pipeline of the standard. In this work, we propose an approach for the reversible pipeline of the JPEG2000 standard. We introduce a new methodology to measure visibility of quantization errors when reversible color and wavelet transforms are employed. Incorporation of the visibility thresholds using this methodology into a JPEG2000 encoder enables creation of scalable codestreams that can provide both near-threshold and numerically lossless representations, which is desirable in applications where restoration of original image samples is required. Most importantly, this is the first work that quantifies the bitrate penalty incurred by the reversible transforms in near-threshold image compression compared to the irreversible transforms.     

基于图像质量检测的智能射线成像技术

X线诊断是一种成熟、有效的检查方法。但是,X线照射过量会损害健康,可能产生随机性效应,如致癌和遗传效应。本文提出基于图像质量检测的智能射线成像系统,利用人眼视觉特性判断图像质量,并以此为指标来控制X线机摄影参数的改变,来实现在获得足够诊断信息的前提下,尽量减少受检者的照射剂量的目的,保障公众的健康与安全。该系统具有很高的可行性与实用性。     

Fast bilateral filter for HDR imaging

Bilateral filtering is a method often used in image processing applications. It is specifically useful for HDR algorithms. A novel approach to a fast and close approximation of bilateral filtering is presented. The method is designed especially with a focus on HDR image conversion into a normal color space processing. This paper presents the methods itself, describes the sources of acceleration and discusses the results of the method.     

Reliable information embedding for image/video in the presence of lossy compression

Lossy compression is inherently contradictory with information hiding and may result in unreliable retrieval of embedded message. For most of the existing data hiding algorithms, the process of dealing with the conflict and trade-off of invisibility, capacity and robustness is done in an experimental fashion. We have developed an image and video unified data-embedding technique. The algorithm is capable of accurately retrieving hidden data after the embedded signals are subjected to JPEG/MPEG compression as long as its compression degree is above the predefined one. Embedding strategy is to integrate data hiding into the JPEG/MPEG coding structures and to combine the adjustment factor of the strength and quantity of data hiding with the control parameter of lossy compression, according to the constraint of human visual system, the demand of hiding capacity and distortion impact of lossy compression. Experimental evaluation demonstrates that the proposed algorithm allows us to hide data invisibly in an accurate retrievable way with effective and flexible trade-off mechanism in the presence of lossy compression. In addition, the scheme is robust to some common attacks including low-pass filtering, noisy interference, frame dropping and transcoding.     

基于图像描述算法的离线盲人视觉辅助系统

针对现有盲人视觉辅助设备存在的不便,探讨了基于模型剪枝的图像描述模型在便携式移动设备上运行的方法。回顾了图像描述模型和剪枝模型技术,重点提出了一种针对图像描述模型的改进剪枝算法。结果表明,在保证准确性的前提下,剪枝后的图像描述模型可以大幅降低工作时的处理时间和消耗的电源容量,能够随时随地快速准确地对环境信息进行描述及语音播报。     

A human visual system-driven image segmentation algorithm

This paper presents a novel image segmentation algorithm driven by human visual system (HVS) properties. Segmentation quality metrics, based on perceptual properties of HVS with respect to segmentation, are integrated into an energy function. The energy function encodes the HVS properties from both region-based and boundary-based perspectives, where the just-noticeable difference (JND) model is employed when calculating the difference between the image contents. Extensive experiments are carried out to compare the performances of three variations of the presented algorithm and several representative segmentation and clustering algorithms available in the literature. The results show superior performance of our approach.     

An embedding strategy on fusing multiple image features for data hiding in multiple images

Data hiding in multiple images has been a significant research direction in information security. How to reasonably design the embedding strategy to spread the payload among multiple images is still an open issue. In this paper, we propose an embedding strategy on fusing multiple features. We utilize the typical characteristic parameters of gray level co-occurrence matrix, the image entropy and the shape parameter to describe image complexity. Furthermore, we combine with the number of cover images, the number of cover images assigned to steganographer and the size of cover image to estimate the steganographic capacity of each image. The strategy is implemented together with some state-of-the-art single image steganographic algorithms. Experimental results demonstrate that the security performance of the proposed strategy is higher than that of the state-of-the-art embedding strategy against the blind universal pooled steganalysis.     

一种基于人眼对比度敏感视觉特性的图像自适应量化方法

为了提高图像的压缩比和压缩质量,结合人眼对比度敏感视觉特性和图像变换域频谱特征,该文提出一种自适应量化表的构建方法。并将该表代替JPEG中的量化表,且按照JPEG的编码算法对3幅不同的彩色图像进行了压缩仿真实验验证,同时与JPEG压缩作对比分析。实验结果表明：与JPEG压缩方法相比,在相同的压缩比下,采用自适应量化压缩后,3幅解压彩色图像的SSIM和PSNR值分别平均提高了1.67%和4.96%。表明该文提出的结合人眼视觉特性的自适应量化是一种较好的、有实用价值的量化方法。