On a predictive scheme for colour image quantization

In this paper we proposed an improved colour image quantization scheme based on predictive coding. Since the neighbouring colour pixels are quite similar in most colour images, the similarity among the encoded pixels is exploited. In the proposed scheme the encoded distinct neighbouring colours are collected to form a smaller state-palette. If the closest colour in the state-palette is quite similar to the current encoding colour pixel, the index of the closest colour in the state-palette is recorded. Otherwise, the closest colour in original colour palette for the current encoding colour pixel is searched and the corresponding index is recorded. The experimental results show that the proposed method achieves good image qualities while requiring much lower bit rates for colour image compression.     

Efficient greyscale image compression technique based on vector quantization

In this paper, a novel greyscale image coding technique based on vector quantization (VQ) is proposed. In VQ, the reconstructed image quality is restricted by the codebook used in the image encoding/decoding procedures. To provide a better image quality using a fixed-sized codebook, the codebook expansion technique is introduced in the proposed technique. In addition, the block prediction technique and the relatively address technique are employed to cut down the required storage cost of the compressed codes. From the results, it is shown that the proposed technique adaptively provides better image quality at low bit rates than VQ.     

像素随机映射的快速算法及在LSB隐藏技术中的应用

提出一种像素随机映射的快速方法, 将该方法与像素字节低位隐藏信息的LSB(Least Significant Bit)技术相结合, 讨论了将RGB彩色图像作为载体隐匿真彩色图像、灰度图像、二值图像及全息信息的方法. 研究结果表明, 该方法加密及解密效率高, 载体图像具有较好的抗破译及抗剪切能力. 根据隐藏信息的性质合理使用LSB技术, 能在基本不影响载体图像质量的情况下较好地隐匿多种信息.     

Adaptive fixed-point iterative shrinkage/thresholding algorithm for MR imaging reconstruction using compressed sensing

Recently compressed sensing (CS) has been applied to under-sampling MR image reconstruction for significantly reducing signal acquisition time. To guarantee the accuracy and efficiency of the CS-based MR image reconstruction, it necessitates determining several regularization and algorithm-introduced parameters properly in practical implementations. The regularization parameter is used to control the trade-off between the sparsity of MR image and the fidelity measures of k-space data, and thus has an important effect on the reconstructed image quality. The algorithm-introduced parameters determine the global convergence rate of the algorithm itself. These parameters make CS-based MR image reconstruction a more difficult scheme than traditional Fourier-based method while implemented on a clinical MR scanner. In this paper, we propose a new approach that reveals that the regularization parameter can be taken as a threshold in a fixed-point iterative shrinkage/thresholding algorithm (FPIST) and chosen by employing minimax threshold selection method. No extra parameter is introduced by FPIST. The simulation results on synthetic and real complex-valued MRI data show that the proposed method can adaptively choose the regularization parameter and effectively achieve high reconstruction quality. The proposed method should prove very useful for practical CS-based MRI applications.     

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.     

Compression of digital holograms via adaptive-sparse representation

Efficient storage and transmission of digital holograms (DHs) requires the development of appropriate compression techniques for such a special class of images. In this Letter, we investigate a method to compress DHs using a sparse matrix representation. Using digital holography to numerically manage complex wave fields, we are able to apply an adaptive mask, based on a threshold filter, to the object wave field. From there, we store the result of this filtering by sparse representation. In this Letter, we demonstrate that using sparse representation allows for a high compression factor with minimal loss in the quality of the reconstructed image. This technique is efficient for storage and transmission of DHs.     

灰度调整与数字全息图像质的关系

如何在有限的灰度级别下输出高质量全息图是人们关注的问题之一.文章从数字全息图 （计算机制全息图）的灰度直方图出发,研究灰度调整对全息图再现像质的影响.首先通过理论推导研究了压缩计算机制全息图中占比例少的灰度,展宽占比例多的灰度后全息图衍射效率的变化,发现处理后的计算机制全息图经灰度压缩的阈值越大,衍射效率越高.然后研究了灰度压缩的阈值对计算机制全息图再现像噪音的影响,发现全息图再现像的噪音随着阈值的增大,先减少再增大.实验表明,通过取合适的阈值对全息图进行灰度调整,可以在保证全息图再现像的信噪比的同时,提高全息图的衍射效率.计算机仿真和全息图光学再现实验证明了理论分析是正确的,为制作高质量的计算机制全息图提供了参考依据.     

Computational integral imaging reconstruction method of 3D images using pixel-to-pixel mapping and image interpolation

In this paper, we propose a novel computational integral imaging reconstruction (CIIR) method to improve the visual quality of the reconstructed images using a pixel-to-pixel mapping and an interpolation technique. Since an elemental image is magnified inversely through the corresponding pinhole and mapped on the reconstruction output plane based on pinhole-array model in the conventional CIIR method, the visual quality of reconstructed output image (ROI) degrades due to the interference problem between adjacent pixels during the superposition of the magnified elemental images. To avoid this problem, the proposed CIIR method generates dot-pattern ROIs using a pixel-to-pixel mapping and substitutes interpolated values for the empty pixels within the dot-pattern ROIs using an interpolation technique. The interpolated ROIs provides a much improved visual quality compared with the conventional method because of the exact regeneration of pixel positions sampled in the pickup process without interference between pixels. Moreover, it can enable us to reduce a computational cost by eliminating the magnification process used in the conventional CIIR. To confirm the feasibility of the proposed system, some experiments are carried out and the results are presented.     

稀疏阈值的超分辨率图像重建

为了解决基于字典学习的超分辨重构算法耗时过长的问题,提出了基于稀疏阈值模型的图像超分辨率重建方法。首先,将联合字典理论与图像块稀疏阈值方法相结合,训练得到高、低分辨率过完备图像字典对。接着,通过稀疏阈值OMP算法对图像特征块进行稀疏表示。然后,通过高分辨率字典重构出初始的超分辨图像。最后,通过改进迭代反投影算法对初始的超分辨图像进行全局优化,从而进一步提高图像重构质量。实验结果表明,超分辨图像重构平均峰值信噪比(PSNR)为30.1 d B,平均结构自相似度(SSIM)为0.937 9,平均计算时间为10.2 s。有效提高了超分辨重构的速度,改善了重构高分辨图像的质量。     

A study on the evaluation of usefulness depending on the image reconstruction method in bone SPECT scan

The recent advances in image-processing techniques have led to the development of many methods to reduce the scan time without degrading the image quality. In particular, tomography has improved image reconstruction methods with the concomitant improvement of high-quality images. In this study, PRECEDENCE 16 was used to reconstruct images using the filtered back projection method, which is generally used, and the Astonish method and three-dimensional ordered-subsets expectation maximization method, which are based on repetition techniques. In qualitative and quantitative analysis of the reconstructed images, a comparison was made between images with different acquisition times and between images with the same acquisition time, which aimed at determining the optimal method for reconstructing high-quality images. A blind test for qualitative analysis confirmed almost no difference in image quality depending on the image acquisition time. Furthermore, in quantitative analysis, there was no significant difference in image quality depending on the image acquisition time. On the other hand, the results of the analysis in the image reconstruction method with the same acquisition time demonstrated a significant difference. The images reconstructed by the Astonish method, which uses a repetition technique, are believed to be excellent because they have high resolution and provide clinical diagnostic information. This study confirmed that the reconstruction method with a repetition technique could be used to improve image quality and reduce the scan time, despite not being in general use until recently due to the lengthy time needed for image reconstruction and lack of storage space.     

An improved fast fractal image compression using spatial texture correlation

This paper utilizes a spatial texture correlation and the intelligent classification algorithm (ICA) search strategy to speed up the encoding process and improve the bit rate for fractal image compression. Texture features is one of the most important properties for the representation of an image. Entropy and maximum entry from co-occurrence matrices are used for representing texture features in an image. For a range block, concerned domain blocks of neighbouring range blocks with similar texture features can be searched. In addition, domain blocks with similar texture features are searched in the ICA search process. Experiments show that in comparison with some typical methods, the proposed algorithm significantly speeds up the encoding process and achieves a higher compression ratio, with a slight diminution in the quality of the reconstructed image; in comparison with a spatial correlation scheme, the proposed scheme spends much less encoding time while the compression ratio and the quality of the reconstructed image are almost the same.     

Demosaicking for multispectral images based on vectorial total variation

Multispectral images (MSIs), which consist of more color components than RGB images, can be used in the field of vegetation analysis and medical imaging. A capturing system with multispectral filter array (MSFA) technology has been researched to shorten the capturing time and reduce the cost. In this system, the mosaicked image captured by the MSFA is demosaicked to reconstruct the MSI. We propose a demosaicking method using vectorial total variation (VTV) regularization for an MSI. This process is regarded as inverse problem of the image observation model. The reconstructed image is estimated by minimizing the VTV as a regularization term under the constraint condition. In the experimental results, the reconstructed image quality obtained using the proposed method is better than that of the conventional approaches in terms of both peak signal-to-noise ratio and structural similarity.     

基于改进型平台直方图的红外均衡化算法

针对红外图像特别是红外弱小目标图像的特点,提出了一种基于改进型平台的直方图均衡算法。在设置统计上限平台阈值的基础上,设置了累计直方图上限阈值,并用修改的映射函数算法对图像进行均衡化处理。算法中的上限统计平台阈值对噪声进行了适当抑制,累计平台阈值自适应控制映射动态范围,从而克服了平台直方图均衡化对动态范围较窄的红外图像过分拉仲的缺点。相对平台直方图的均衡算法,该方法能够对多种复杂场景增强图像整体效果,在抑制噪声的同时较好地保持了图像细节。     

相位差波前探测与图像重建

相位差技术可以直接利用两幅或多幅图像的强度信息,重构出波前相位信息和目标清晰图像,具有光路简单、成本较低、适用于扩展目标等优点,在望远镜的系统像差检测和目标图像重建方面得到了大量应用。相位差波前探测的关键在于求解非线性代价函数的最优化问题,需要避免陷入局部极值并降低计算时间,才能满足动态变化波前实时探测的需求。同时在重建目标清晰图像时,通常需要做正则化和去噪处理,来提高重建图像的质量。本文主要介绍相位差技术的基本原理,以及近年来的研究进展,并对该技术未来的发展进行了展望。     

Enhancement of low-quality reconstructed digital hologram images based on frequency extrapolation of large objects under the diffraction limit

During the reconstruction of a digital hologram, the reconstructed image is usually degraded by speckle noise, which makes it hard to observe the original object pattern. In this paper, a new reconstructed image enhancement method is proposed, which first reduces the speckle noise using an adaptive Gaussian filter, then calculates the high frequencies that belong to the object pattern based on a frequency extrapolation strategy. The proposed frequency extrapolation first calculates the frequency spectrum of the Fourier-filtered image, which is originally reconstructed from the +1 order of the hologram, and then gives the initial parameters for an iterative solution. The analytic iteration is implemented by continuous gradient threshold convergence to estimate the image level and vertical gradient information. The predicted spectrum is acquired through the analytical iteration of the original spectrum and gradient spectrum analysis. Finally, the reconstructed spectrum of the restoration image is acquired from the synthetic correction of the original spectrum using the predicted gradient spectrum. We conducted our experiment very close to the diffraction limit and used low-quality equipment to prove the feasibility of our method. Detailed analysis and figure demonstrations are presented in the paper.     

自由基聚合型光致聚合物中全息图像质量的动态特性研究

用实验方法研究了光致聚合物中全息存储再现图像质量的动态特性,以信噪比损失作为图像质量变化的衡量指标,进行了暗增长和均匀后曝光过程监测图像实验。实验结果表明,在暗增长和均匀后曝光过程中,再现图像强度和质量经历先增长后下降的动态过程。以噪声光栅的形成和发展对实验结果进行了初步的解释。以信噪比损失不大于3 dB为判据考察了全息图对暗反应和均匀后曝光过程的宽容程度,对于不同的记录条件确定了暗反应和均匀后曝光过程的特征时间。在特征时间内,再现图像的质量和强度都是可以接受的。在复用记录时,为保证所有全息图有均衡的衍射效率和良好的图像质量,必须考虑再现图像质量和强度的动态变化因素。     

光子计数集成成像的压缩与重构

集成成像技术作为一种重要的裸眼三维显示技术,在完整记录三维场景信息的同时,庞大的数据量给传输和存储带来了压力。为了实现图像的有效压缩和重构,根据光子计数集成成像的特点,基于分布式压缩感知理论,提出用于图像压缩与重构的方案。该方案将图像分为参考图像和非参考图像两类,对其设置不同的测量率并分别进行重构。为保证非参考图像的重构质量,提出一种联合重构算法。该算法首先对非参考图像进行分块测量,依据与参考图像之间的相关性进行图像块分类,然后结合参考图像测量值信息构建新的测量矢量,利用新的测量矢量完成初次图像重构。为了进一步提升图像重构质量,对初次重构结果进行二次残差补偿重构,获得最终重构结果。最后通过设置不同的测量率进行了大量实验,实验结果表明,所提算法在测量率为0.25时,图像重构质量可以达到30 dB,测量率为0.4时,图像质量可以达到35 dB,算法性能具有一定的优越性。     

增强型双通道实时联想存储系统的研究

首次将多通道并行处理的概念引入联想存储系统中，提出一个带有ＣＣＤ摄像机、图像卡、微机及液晶光阈等控制与输入设备，并以液晶电光开关作为取阈反馈装置的双通道联想系统。系统存储方式采用计算机磁盘充当外部图像库存储大量参考图像，而在系统内一点只存储一幅图像。     

基于压缩感知的动态散射成像

利用基于压缩感知的成像系统可以透过静态的散射介质获得高质量的重建图像. 但是当散射介质动态变化时, 因为采样所得的测量值受到散射介质衰减系数非线性变化的影响, 重建图像质量会大大下降. 针对上述情况, 本文提出基于压缩感知成像系统的测量值线性拉伸算法, 该算法能够对所得到的非线性测量值进行分析, 根据测量值大小的不同将测量值划分成数个区域并计算补偿系数, 从而根据补偿系数进行测量值线性拉伸变换, 使测量值线性化. 最后再对变换后的测量值进行压缩感知重建计算. 通过理论分析、计算机仿真和实验证明了所提算法能够有效地应对动态的散射介质, 提高基于压缩感知成像系统在透过动态散射介质时的图像重建质量.     

Design of adaptive spatial filter at uniform standard for automatic analysis of digital holographic microscopy

The spatial filtering method is a useful technique for the dynamic and automatic analysis in digital holographic microscopy. It has been shown that the proper selection of the spatial filter would improve the quality of the reconstructed image. However different results would be obtained by employing the spatial filter with different parameter threshold decided at different standard. This paper, according to the histogram analysis of the distribution of the +1 term spectrum of each hologram, gropes for the uniform standard for the decision of the threshold of the adaptive filter. It helps the adaptive spatial filtering method to be more advantageous for the dynamic and automatic analysis.