Efficient compression of motion-compensated sub-images with Karhunen-Loeve transform in three-dimensional integral imaging

An approach to highly enhance the compression efficiency of the integral images by applying the Karhunen-Loeve transform (KLT) algorithm to the motion-compensated sub-images is proposed. The sub-images transformed from the elemental images picked-up from the three-dimensional (3D) object might represent the different perspectives of the object. Thus, the similarity among the sub-images gets better than that among the elemental images, so that an improvement of compression efficiency of the sub-images could be obtained. However, motion vectors occurred among the sub-images might result in an additional increase of image data to be compressed. Accordingly, in this paper, motion vectors have been estimated and compensated in all sub-image in advance. Then the KLT algorithm was applied to these motion-compensated sub-images for compression. It is shown from some experimental results that compression efficiency of the proposed method has been improved up to 24.44%, 40.62%, respectively, on the average compared to that of the conventional KLT compression method and that of the JPEG.     

Efficient compression of rearranged time-multiplexed elemental image arrays in MALT-based three-dimensional integral imaging

In this paper, an approach to efficiently compress the time-multiplexed EIAs picked up from the MALT-based integral imaging system is proposed. In this method, the time-multiplexed EIAs are rearranged by collecting the elemental images occupied at the same position in each EIA to enhance the similarity among the elemental images. Then, MPEG-4 is applied to these rearranged elemental images for compression. From the experimental results, it is shown that the average correlation quality (ACQ) value representing a degree of similarity between the elemental images, and the resultant compression efficiency have been enhanced by 11.50% and 9.97%, respectively on the average for three kinds of test scenarios in the proposed method, compared to those of the conventional method. Good experimental results finally confirmed the feasibility of the proposed scheme.     

Compression scheme of sub-images using Karhunen-Loeve transform in three-dimensional integral imaging

In this paper, a compression scheme of sub-image-transformed elemental images using Karhunen-Loeve transform (KLT) in three-dimensional integral imaging is proposed. The proposed scheme provides improved compression efficiency by improving the similarity between elemental images using sub-image transformation. To test the proposed scheme, various elemental images of 3D objects are picked up and the compression process is carried out using KLT. From the experimental results, it is showed that the proposed compression scheme gives us an improved efficiency of 26% as compared with the conventional compression method.     

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。     

Robust image encryption by combined use of integral imaging and pixel scrambling techniques

A robust image encryption method by using the integral imaging and pixel scrambling (PS) techniques is proposed. In this method, pixels of the cover image are scrambled with the PS technique and elemental images for this scrambled image are picked up through a lenslet array. Subsequently, an encrypted image is obtained by scrambling these picked-up elemental images. Since this encrypted image has the hologram-like property of data redundancy resulted from the integral imaging scheme, while it can as well be decoded by multiple keys such as the orders of pixel scrambling and the pickup conditions of the elemental images, its security against the various attacks could be dramatically improved. Good experimental results also confirm that the proposed method could provide more enhanced robustness against data loss and Gaussian noises compared to the conventional methods.     

Three-dimensional image authentication using binarized images in double random phase integral imaging

We proposed a three-dimensional(3D) image authentication method using binarized phase images in double random phase integral imaging(InI). Two-dimensional(2D) element images obtained from InI are encoded using a double random phase encryption(DRPE) algorithm. Only part of the phase information is used in the proposed method rather than using all of the amplitude and phase information, which can make the final data sparse and beneficial to data compression, storage, and transmission. Experimental results verified the method and successfully proved the developed 3D authentication process using a nonlinear cross correlation method.     

Resolution-enhanced 3D image correlator using computationally reconstructed integral images

In this paper, a novel resolution-enhanced three-dimensional (3D) image correlator using the computationally reconstructed integral images is proposed in order to extract target object’s 3D location data in a scene. Elemental images of the reference and target objects are picked up by lenslet arrays and using these elemental images, reference and target plane images are reconstructed on the output plane by means of a modified computational integral imaging reconstruction technique. Then, through cross-correlations between the reconstructed reference and the target plane images, 3D location data of the target object can be extracted from the correlation outputs. With the purpose of showing the feasibility of the proposed method, some computational and optical experiments on the target objects in space are carried out and the results are presented.     

基于自适应量化的超光谱图像压缩

提出了一种基于谱间预测和小波量化编码的超光谱图像压缩方法。在充分考虑子带图像非平稳特性的基础上,首先实现了子带分类步骤,通过分类设计自适应预测器,提高了谱间去相关效率。由于子带中不同子类表现出了不同的统计特性,所以使用空变均匀阈值量化器完成了量化工作。研究了均匀量化器对不同分布训练样本的率 失真表现,并为相关特性建立了模型描述。基于率失真模型和系数序列的统计特性,提出了一个率分配算法,以便能为不同的子类系数序列设计率失真意义上的最优量化器。实验证明,这种方法能高效地压缩超光谱图像,表现出了优异的压缩性能。     

基于四叉树和偏微分方程的灰度图像压缩

提出了一种基于四叉树和偏微分方程的灰度图像压缩方法。该方法只需传输和处理部分稀疏像素而不是整幅灰度图像。在编码端,首先采用四叉树分割图像,然后对部分像素进行编码传输。在解码端,采用基于偏微分方程的图像插值算法再生图像,有效地消除了解码图像中的方块效应。实验表明,该方法可以获得较高的压缩比和峰值信噪比,尤其是对尺寸较大且纹理细节较少的图像更是如此,并能较好地保持原始图像中灰度变化较大的细节,可以方便地去除方块效应,具有较高的实用价值。     

基于提升方案的多光谱遥感图像有损压缩算法

在分析多光谱遥感图像谱间和空间数据特点的基础上,提出了一种DPCM线性预测与基于提升方案的整数小波变换相结合的多光谱遥感图像有损压缩算法。在谱间采用DPCM预测去除谱间相关性;在谱内采用整数小波变换去除空间相关性,根据不同子带对目标识别的重要程度,选择不同的量化阈值和量化步长进行量化,并分别对各个子带量化后的数据和重要图表采用固定比特平面编码和游程编码,实现高效的多光谱遥感图像压缩。实验结果表明,该算法在一定的压缩比下,重构图像具有较高的峰值信噪比,并且算法硬件实现简单,对内存的需求低。     

Occlusion removal technique for improved recognition of partially occluded 3D objects in computational integral imaging

In this paper, we propose an occlusion removal technique for improved recognition of 3D objects that are partially occluded in computational integral imaging (CII). In the reconstruction process of a 3D object which is partially occluded by other objects, occlusion degrades the resolution of reconstructed 3D images and thus this affects negatively the recognition of a 3D object in CII. To overcome this problem, we introduce a method to eliminate occluding objects in elemental image array (EIA) and the proposed method is applied to 3D object recognition by use of CII. To our best knowledge, this is the first time to remove occlusion in CII. In our method, we apply the elemental image to sub-image (ES) transform to EIA obtained by a pickup process and those sub-images are employed for occlusion removal. After the transformation, we correlate those sub-images with a reference sub-image to locate occluding objects and then we eliminate the objects. The inverse ES transform provides a modified EIA. Actually, the modified EIA is considered to be an EIA without the object that occludes the object to be reconstructed. This can provide a substantial gain in terms of the image quality of 3D objects and in terms of recognition performance. To verify the usefulness of the proposed technique, some experimental results are carried out and the results are presented.     

High dynamic range compression and detail enhancement of infrared images in the gradient domain

To find the trade-off between providing an accurate perception of the global scene and improving the visibility of details without excessively distorting radiometric infrared information, a novel gradient-domain-based visualization method for high dynamic range infrared images is proposed in this study. The proposed method adopts an energy function which includes a data constraint term and a gradient constraint term. In the data constraint term, the classical histogram projection method is used to perform the initial dynamic range compression to obtain the desired pixel values and preserve the global contrast. In the gradient constraint term, the moment matching method is adopted to obtain the normalized image; then a gradient gain factor function is designed to adjust the magnitudes of the normalized image gradients and obtain the desired gradient field. Lastly, the low dynamic range image is solved from the proposed energy function. The final image is obtained by linearly mapping the low dynamic range image to the 8-bit display range. The effectiveness and robustness of the proposed method are analyzed using the infrared images obtained from different operating conditions. Compared with other well-established methods, our method shows a significant performance in terms of dynamic range compression, while enhancing the details and avoiding the common artifacts, such as halo, gradient reversal, hazy or saturation.     

基于小波变换与小域特征模糊融合的人脸识别

小波变换是一种很好的图像压缩方法,利用小波变换对人脸图像进行三次小波分解,并将低频分量分割成为7个子图像。鉴于人脸上的各小域子图像信息的相互独立性。先利用小域子图像实现软分类,然后使用传统奇异值分解(SVD)法提取出各小域子图像的奇异值(SV),构造出小域奇异值特征向量,给出待识别图像对训练样本图像的隶属度,并采用模糊融合的方法对小域特征进行数据融合,获得识别结果。实验结果表明,该方法实现起来简单、识别速度快,具有很高的识别率。     

基于网格编码量化的超光谱图像压缩

提出了一个基于小波网格编码量化的超光谱图像压缩方法。谱间和空间冗余处理构成了超光谱图像压缩算法的主要内容,该算法使用一个谱间差分预测步骤来去除谱间冗余,而后对预测残差图像进行小波变换并利用均匀阈值网格编码量化(trellis-coded quantization)方法来量化各小波子带,最后使用自适应算术编码对量化码字进行熵编码。为使编码器能为所有子带获取率-失真意义上最优的量化阈值,设计了一个基于子带统计特性和网格编码量化器率-失真特性的比特分配算法。在实验中,该算法表现出优良的压缩性能,对于实验的超光谱图像,该方法在压缩比为32时可得到37．1dB的峰值信噪比,这表明本算法能有效压缩超光谱图像,适于超光谱图像压缩应用。     

Removal of residual images in parallel phase-shifting digital holography

Parallel phase-shifting digital holography (PPSDH) is a technique of single-shot phase-shifting digital holography. We found that there are two problems with this technique. (1) Some extraneous noises caused by the intensity unevenness of the reference wave become slightly superimposed on the object image. (2) The conjugate image cannot be completely removed. This is because the object wave causes the phase-shift error by illuminating an image sensor with a large incident angle. To solve these problems, we propose an algorithm for removing residual 0th-order diffraction and conjugate images in PPSDH. In the proposed algorithm, we modified phase-shifting interferometry in order to work through the unevenness of the intensity distribution and applied the Fourier transform technique to PPSDH to remove the residual conjugate image. The effectiveness of the proposed algorithm was experimentally verified.     

一种基于Mumford-Shah模型的红外图像边缘检测方法

 Chan-Vese模型是一种优秀的简化Mumford-Shah模型。然而Chan-Vese模型是以两个同质区域为基础建立的，这并不符合红外图像的特点，导致直接应用该模型处理红外图像时可能失败。针对这一问题，提出了一种适用于红外图像边缘检测的改进Mumford-Shah模型，并对该模型中目标边缘的保持、停止准则的建立及算法速度的提高作了详细讨论。实验表明，改进Mumford-Shah模型能够克服Chan-Vese模型在对红外图像边缘检测时不能跨越过渡区域的缺点，有效地检测出目标边缘。     

Processing a sequence of images for super-resolution problem solving

An algorithm is proposed that is capable of processing a sequence of images so as to increase their resolution and overcome restrictions imposed by a finite number of sensitive elements in the radiation detector. The image size is increased using a spectral interpolation method. A method of selecting reference frames and determining interframe displacement vectors is described. Results of application of the proposed algorithm to real images are presented.     

Best tree wavelet packet transform based copyright protection scheme for digital images

In this paper, a dual watermarking scheme based on discrete wavelet transform (DWT), wavelet packet transform (WPT) with best tree, and singular value decomposition (SVD) is proposed. In our algorithm, the cover image is sub-sampled into four sub-images and then two sub-images, having the highest sum of singular values are selected. Two different gray scale images are embedded in the selected sub-images. For embedding first watermark, one of the selected sub-image is decomposed via WPT. The entropy based algorithm is adopted to find the best tree of WPT. Watermark is embedded in all frequency sub-bands of the best tree. For embedding second watermark, l-level discrete wavelet transform (DWT) is performed on the second selected sub-image. The watermark is embedded by modifying the singular values of the transformed image. To enhance the security of the scheme, Zig-Zag scan in applied on the second watermark before embedding. The robustness of the proposed scheme is demonstrated through a series of attack simulations. Experimental results demonstrate that the proposed scheme has good perceptual invisibility and is also robust against various image processing operations, geometric attacks and JPEG Compression.     

Modified smart pixel mapping method for displaying orthoscopic 3D images in integral imaging

In this paper, we propose a modified smart pixel mapping (MSPM) method for displaying orthoscopic three-dimensional (3D) images with a function of depth control in integral imaging system. In the proposed MSPM, the depth-converted elemental image array (EIA) is obtained through the pixel mapping process and the image interpolation technique. The proposed method gives us the depth conversion at distances different from the position of 3D object and provides various types of EIAs using only an original EIA for orthoscopic images. To show the usefulness of the proposed method, we carry out the preliminary experiments and present the experimental results.     

Cryptanalysis and improvement of a binary watermark-based copyright protection scheme for remote sensing images

The copyright protection of the remote sensing images is becoming a hot research topic in recent years. By considering the characteristics of the binary image, Zhu et al. proposed a new digital watermarking algorithm to protect the copyright of remote sensing images effectively. However, Zhu et al.’s scheme is not secure under the novel attack method proposed in this paper. While keeping the visual quality of the protected original image unchanged, the embedded watermark can be replaced with another watermark if the attacker has the host image carrying the other watermark. Thus the copyright of the original image changes and the copyright protection fail. To overcome the insecurity, a chaos-based improvement measure is proposed, in which the performance is the same as before. Analysis, proof, and experiment show that our methods are feasible and effective.