Improved vector quantization scheme for grayscale image compression

This paper proposes an improved image coding scheme based on vector quantization. It is well known that the image quality of a VQ-compressed image is poor when a small-sized codebook is used. In order to solve this problem, the mean value of the image block is taken as an alternative block encoding rule to improve the image quality in the proposed scheme. To cut down the storage cost of compressed codes, a two-stage lossless coding approach including the linear prediction technique and the Huffman coding technique is employed in the proposed scheme. The results show that the proposed scheme achieves better image qualities than vector quantization while keeping low bit rates.     

改进自适应LBG矢量量化算法在干涉高光谱图像压缩中的应用

在基于点到线模型扩展LBG(linde-buzo-gray algorithm)矢量量化算法的基础上,提出了一种更为高效的新型自适应LBG矢量量化算法,并给出了该算法在干涉高光谱图像无损压缩中的实际压缩方案.该算法在LBG算法码书中利用点到线的垂线关系基础上进行了改进,执行进一步的自适应化迭代进而获得了更小的残差.将自...     

Image enlargement with high-frequency component augmentation based on predefined codebook describing edge blurring properties

Image super-resolution as high-quality image enlargement is achieved by some type of restoration for high-frequency components that deteriorate through the image enlargement. The estimation methods using the given image itself are effective for the restoration, and we have proposed a method employing the codebook describing edge blurring properties that are derived from the given image. It is, however, unfavourable to apply those image-dependent methods to movies whose scene varies momentarily. In this paper, an image-independent codebook incorporating local edge patterns of images is proposed, and then the predefined codebook is applied. The effectiveness is shown through some experiments.     

Image super-resolution based on local self-similarity

A new image super-resolution method based on a codebook mapping is proposed. The codebook mapping represents the internal relationship between low-and high-frequency image components, and is used for the estimation of highfrequency image components lost in the sampling process. In the proposed method, codebooks are first generated by the low-and high-frequency image components of the original image itself that is to be processed. Then, a resultant superresolution image, that is, an enlarged image, is obtained by combining the estimated high-frequency image components with the low-frequency ones obtained by a typical interpolation-based method. The effectiveness of the proposed method is verified by comparing it against some conventional methods.     

A hybrid quantum encoding algorithm of vector quantization for image compression

Many classical encoding algorithms of vector quantization (VQ) of image compression that can obtain global optimal solution have computational complexity O(N). A pure quantum VQ encoding algorithm with probability of success near 100% has been proposed, that performs operations 45\sqrt{N} times approximately. In this paper, a hybrid quantum VQ encoding algorithm between the classical method and the quantum algorithm is presented. The number of its operations is less than \sqrt{N} for most images, and it is more efficient than the pure quantum algorithm.     

A block-based watermarking scheme for image tamper detection and self-recovery

In this paper, we present an effective block-based digital fragile watermarking scheme for image tamper detection and recovery. The proposed scheme embeds watermarks consisting of the authentication data and the recovery data into image blocks. It adopts parity check and the intensity-relation check to thwart various malicious attacks. In the tamper detection process, instead of independently testing the embedded authentication data of each block, we take the block-neighbourhood into account and utilize a hierarchical structure to determine the legitimacy of image blocks. Experimental results show that the proposed scheme can effectively resist collage attack, vector quantization (VQ) attack and constant-average attack, while sustaining superior accuracy of tamper localization. Furthermore, the results reveal that the tampered images can be successfully self-recovered with acceptable visual quality.     

A novel data hiding and reversible scheme using SMN blocks in VQ-compressed images

Data hiding is a technique for embedding secret data into cover media. It is important to multimedia security and has been widely studied. Reversible data hiding methods are becoming prevalent in the area because they can reconstruct the original cover image while extracting the embedded data. In this paper, we propose a new reversible method for vector quantization (VQ) compressed images. Our method takes advantages of the relationship among the side match neighbouring (SMN) blocks to achieve reversibility. The experimental results show that the proposed method has higher compression rate and larger capacity than other existing reversible methods.     

An adaptive VQ method used on interferential multi-spectral image lossless compression

In this paper, a high efficient adaptive LBG VQ (vector quantization) method is proposed, which is an improved version of the expansion LBG VQ method [1] (proposed in 2009)and exploits the shortest distance from a point to line segment. Moreover, the proposed method is used on the lossless compression of LASIS (Large Aperture Static Imaging Spectrometer) interferential multi-spectral images. Compared with the expansion LBG VQ method proposed in 2009, the experimental results showed that the adaptive LBG VQ method improved the compression performance obviously. And the experiment also showed that when using these LBG VQ methods above without Dual-Direction Prediction [2], the entropy generated by expansion LBG VQ method [1] sometimes will be larger than that generated by traditional LBG VQ method [3], and when using these LBG VQ methods above after Dual-Direction Prediction [2], CR (compression ratio) generated by expansion LBG VQ method [1] sometimes will be less than that generated by traditional LBG VQ method [3], while the entropy generated by the method proposed in this paper will be much less than that generated by either traditional LBG VQ method [3] or the expansion LBG VQ method [1], and CR generated by the method proposed in this paper will be much larger than that generated by either traditional LBG VQ method [3] or the expansion LBG VQ method [1].     

混合激励线性预测语音编码标准中线谱频率量化的研究

线谱频率(Line Spectral Frequency,LSF)是线性预测频谱系数(Linear Predication Coefficient,LPC)有效的编码形式。语音线性预测模型中,LPC反映了声道调制的模型,是影响语音听觉感知重要的参数之一。在混合激励线性预测语音编码(Mixed Excitation Linear Prediction,MELP)标准中,对LSF采用4级码本进行分级式矢量量化。首先,为减少其量化冗余度以降低编码速率,本文提出了一种改进的选择算法,生成了一个2级码本替换之。其次,为提高合成语音质量,依据LSF矢量量化的精度与合成语音质量的关系的实验结果,提出根据人耳听觉感知特性进行LSF量化和评价的方法,并予以实验证明。     

Fast image enlargement using predefined codebook and eigenspace backprojection for lost pixel

In this paper, a new image enlargement method applying the backprojection for lost pixel (BPLP) to the predefined codebook-based method is proposed. BPLP is a method for image restoration. In BPLP, the eigenspace reflecting the characteristics of an input image is generated from the remained pixels and is used to restore the missing pixels. In the proposed method, the eigenspace is replaced by one generated from the predefined codebook (PDC). PDC represents edge-blurring properties in a small image patch and consists of pairs of low- and high-frequency image patches on various edge patterns. By replacing the PDC-based estimation of lost high-frequency components with BPLP, a fast image enlargement method retaining its performance can be developed. Through some experiments, the effectiveness of the proposed method was demonstrated. Especially, it was confirmed that the processing time of the proposed method was shortened to about 1/50 that of the PDC-based method.     

四光束剪切相干成像目标重构算法研究

针对传统剪切光束成像技术的准实时性问题,提出用口字形排布的四束光代替传统L形三束剪切光照射目标,研究了四光束剪切相干成像目标重构算法.只需单次测量就能同时重构出四幅目标图像,减少了用于降低散斑噪声、获取高质量图像所需的测量次数,同时大大减少了多组发射时的光束切换次数,提高了成像效率.在算法实现中,通过最小二乘法恢复出四组波前相位,利用散斑幅值的简单代数运算恢复波前幅值,从而重构出目标图像.仿真结果表明,与传统方法相比,在图像质量相同的前提下,本文方法所需的数据采集时间减少了至少1/2,不但提高了目标重构效率,还可为远程运动目标的成像识别提供更好的手段.     

Improved algorithm for image encryption based on stochastic geometric moiré and its application

A technique based on optical operations on moiré patterns for image encryption and decryption is developed. In this method, an image is encrypted by a stochastic geometric moiré pattern deformed according to the image reflectance map. The decryption is performed using pixel correlation algorithm in the encrypted image and the stochastic geometrical moiré pattern. The proposed technique has a number of advantages over existing encryption techniques based on moiré gratings. No original moiré grating can be reconstructed only from the encrypted image. Stochastic moiré grating can be deformed in any direction what is an important factor of encryption security. Finally, the quality of the decrypted image is much better compared to decryption methods based on the superposition of the regular and deformed moiré gratings. The proposed technique has a great potential, because the process is performed using computational algorithms based on optical operations and optical components are avoided.     

基于双线空间像线宽不对称度的彗差测量技术

在高数值孔径、低工艺因子的光刻技术中,投影物镜彗差对光刻质量的影响变得越来越突出,因而需要一种快速、高精度的彗差原位测量技术。为此提出了一种新的基于双线空间像线宽不对称度的彗差测量技术,利用国际上公认的半导体行业光刻仿真软件PROLITH对该方法的测量精度进行了仿真分析。结果表明,与基于硅片曝光的彗差测量方法相比,基于空间像的彗差测量技术速度上的优势十分明显。其测量精度优于1.4 nm,较国际前沿的多照明设置空间像测量技术(TAMIS)提高30%以上,测量速度提高1/3左右。在ASML公司的PAS5500型步进扫描投影光刻机上,多次测量了投影物镜彗差,结果表明,该技术测量重复精度优于1.2 nm,能实现高精度的彗差原位测量。     

Color correction for high dynamic range images using a chromatic adaptation method

In the image capturing process using a camera, poor illumination has an influence on the image quality, especially in regards to the contrast and details in the dark regions. Generally, high dynamic range (HDR) imaging techniques are used to match the quality between the real scene and the displayed image. However, in images using the multi-exposure technique or regular photography, the images are limited by the veiling glare, which is scene-, exposure-, lens-, aperture-, and camera-dependent. This study mainly addressed images using the multi-exposure technique and developed a color correction scheme that uses a chromatic adaptation method. In the tone mapping using a Gaussian pyramid, the adaptation level is obtained based on a linear Gaussian filter. The resulting image is then processed through the developed tone-mapping function. This allows the chromatic adaptation method to address the mismatches between the real world and the displayed image. The experiment results show that the proposed method yields a better color correction performance compared to conventional methods.     

A novel FOCAL technique based on BP-ANN

In this paper, the feed-forward back-propagation artificial neural network (BP-ANN) algorithm is introduced in the traditional Focus Calibration using Alignment procedure (FOCAL) technique, and a novel FOCAL technique based on BP-ANN is proposed. The effects of the parameters, such as the number of neurons on the hidden-layer and the number of training epochs, on the measurement accuracy are analyzed in detail. It is proved that the novel FOCAL technique based on BP-ANN is more reliable and it is a better choice for measurement of the image quality parameters.     

Infrared image enhancement using Cellular Automata

Image enhancement is a crucial technique for infrared images. The clear image details are important for improving the quality of infrared images in computer vision. In this paper, we propose a new enhancement method based on two priors via Cellular Automata. First, we directly learn the gradient distribution prior from the images via Cellular Automata. Second, considering the importance of image details, we propose a new gradient distribution error to encode the structure information via Cellular Automata. Finally, an iterative method is applied to remap the original image based on two priors, further improving the quality of enhanced image. Our method is simple in implementation, easy to understand, extensible to accommodate other vision tasks, and produces more accurate results. Experiments show that the proposed method performs better than other methods using qualitative and quantitative measures.     

使用计算全息进行三维信息加密的方法研究

全息加密技术作为一种特殊的加密方法被广泛应用于信息加密和防伪等领域。在全息加密过程中,光波的波长、记录距离和入射角度等参数用做加密密钥和解密密钥被人们深入研究,但所加密的信息几乎都是二维信息。利用一种基于虚拟光学的对三维信息进行加密的方法,将三维物体的大小作为一个新的密钥被引入安全全息加密算法,其安全性能得到了极大提高;在此基础上提出了对再现三维图像进行客观评价的方法,即修正峰值信噪比法(PSNR,PeakSignal-to-Noise Ratio)。模拟实验证明,计算全息方法(CGH,Computer-Generated Hologram)作为一种对三维信息进行加密的方法是可行的,修正PSNR法对再现三维图像的质量进行定量分析是有效的。     

Vision-based weld pool boundary extraction and width measurement during keyhole fiber laser welding

In keyhole fiber laser welding processes, the weld pool behavior is essential to determining welding quality. To better observe and control the welding process, the accurate extraction of the weld pool boundary as well as the width is required. This work presents a weld pool edge detection technique based on an off axial green illumination laser and a coaxial image capturing system that consists of a CMOS camera and optic filters. According to the difference of image quality, a complete developed edge detection algorithm is proposed based on the local maximum gradient of greyness searching approach and linear interpolation. The extracted weld pool geometry and the width are validated by the actual welding width measurement and predictions by a numerical multi-phase model.     

Model-based speech enhancement using a bone-conducted signal

Codebook-based single-microphone noise suppressors, which exploit prior knowledge about speech and noise statistics, provide better performance in nonstationary noise. However, as the enhancement involves a joint optimization over speech and noise codebooks, this results in high computational complexity. A codebook-based method is proposed that uses a reference signal observed by a bone-conduction microphone, and a mapping between air- and bone-conduction codebook entries generated during an offline training phase. A smaller subset of air-conducted speech codebook entries that accurately models the clean speech signal is selected using this reference signal. Experiments support the expected improvement in performance at low computational complexity.