A systolic algorithm for hidden surface removal

With the advent of VLSI it has become possible to map parallel algorithms for compute-bound problems directly on silicon. Systolic architecture is very good candidate for VLSI implementation because of its regular and simple design, and regular communication pattern. In this paper, a systolic algorithm and corresponding systolic architecture, a linear systolic array, for the scanline-based hidden surface removal problem in three-dimensional computer graphics have been proposed. The algorithm is based on the concept of sample spans or intervals. The worst case time taken by the algorithm is O(n), n being the number of segments in a scanline. The time taken by the algorithm for a given scene depends on the scene itself, and on an average considerable improvement over the worst case behaviour is expected. A pipeline scheme for handling the I/O process has also been proposed which is suitable for VLSI implementation of the algorithm.     

A systolic algorithm for Euclidean distance transform

The Euclidean distance transform is one of the fundamental operations in image processing. It has been widely used in computer vision, pattern recognition, morphological filtering, and robotics. This paper proposes a systolic algorithm that computes the Euclidean distance map of an N /spl times/ N binary image in 3N clocks on 2N/sup 2/ processing cells. The algorithm is designed so that the hardware resources are reduced; especially no multipliers are used and, thus, it facilitates VLSI implementation.     

Greylevel Difference Classification Algorithm in Fractal Image Compression

This paper propses the notion of a greylevel difference classification algorithm in fractal image compression .Then an example of the greylevel difference classification alge-rithm is given as an improvement of the quadrant grevlevel and variance classification in the quadtree-based encoding algorithm.The algorithm incorporates the frequency feature in spatial analysis using th notion of average quadrant greylevel difference,leading to an enhancement in terms of encoding time ,PSNR value and compression ratio.     

基于双分量差值扩展的彩色图像可擦除水印*

针对Tian算法中过度利用差值造成含印图像质量下降严重的问题,提出了基于双分量差值扩展的彩色图像可擦除水印算法。该算法将差值扩展量分散到四个灰度值中,含印图像质量明显提高。实验表明,该方法嵌入的水印不可见性好,擦除水印的图像与原始图像完全相同,适合于图像的精确认证和窜改定位。     

基于差值域直方图平移的密文可逆水印算法

为了满足密文域水印可逆嵌入的需要,利用一种直方图平移与同态加密相结合的技术,提出了一种新颖的差值域直方图平移密文图像可逆水印算法.该算法可以在没有原始图像信息的情况下直接对密文域图像嵌入水印,即实现原始图像—加密—水印嵌入的过程,从而简化了传统算法中原始图像—加密—解密—水印嵌入—加密的冗余过程.仿真实验表明,该算法可以在图像失真度很低的情况下,有效提高嵌入容量,而且水印完全提取,图像无失真恢复.实验效果明显好于其他算法.     

A systolic algorithm for riccati and lyapunov equations

Riccati and Lyapunov equations can be solved using the recursive matrix sign method applied to symmetric matrices constructed from the corresponding Hamiltonian matrices. In this paper we derive an efficient systolic implementation of that algorithm where theLDL ^T andUDU ^T decompositions of those symmetric matrices are propagated. As a result the solution of a class of Riccati and Lyapunov equations can be obtained inO(n) time steps on a bidimensional (triangular) grid ofO(n ²) processors, leading to an optimal speedup.     

A new difference image creation method based on deep neural networks for change detection in remote-sensing images

In this article, we propose a novel difference image (DI) creation method for unsupervised change detection in multi-temporal multi-spectral remote-sensing images based on deep learning theory. First, we apply deep belief network to learn local and high-level features from the local neighbour of a given pixel in an unsupervised manner. Second, a back propagation algorithm is improved to build a DI based on selected training samples, which can highlight the difference on changed regions and suppress the false changes on unchanged regions. Finally, we get the change trajectory map using simple clustering analysis. The proposed scheme is tested on three remote-sensing data sets. Qualitative and quantitative evaluations show its superior performance compared to the traditional pixel-level and texture-level-based approaches.     

A systolic algorithm for solving dense linear systems

For an arbitrary n × n matrix A and an n × 1 column vector b, we present a systolic algorithm to solve the dense linear equations Ax = b. An important consideration is that the pivot row can be changed during the execution of our systolic algorithm. The computational model consists of n linear systolic arrays. For 1 ≤ i ≤ n, the i^th linear array is responsible to eliminate the i^th unknown variable x_i of x. This algorithm requires 4n time steps to solve the linear system. The elapsed time unit within a time step is independent of the problem size n. Since the structure of a PE is simple and the same type PE executes the identical instructions, it is very suitable for VLSI implementation. The design process and correctness proof are considered in detail. Moreover, this algorithm can detect whether A is singular or not.     

An image contrast enhancement algorithm for grayscale images using particle swarm optimization

This paper addresses a contrast enhancement technique that combines classical contrast enhancement with an evolutionary approach. The central goal of this work is to increase the information content and enhance the details of an image using an adaptive gamma correction technique aided by particle swarm optimization. Gamma correction is a well established technique that preserves the mean brightness of an image that produces natural looking images by the choice of an optimal gamma value. Here, Swarm intelligence based particle swarm optimization is employed to estimate an optimal gamma value. In the proposed method, the edge and information content (entropy) are the parameters used to formulate the fitness function. The proposed method is compared with state-of-the-art of techniques in terms of Weighted Average Peak Signal to Noise Ratio (WPSNR), Contrast, Homogeneity, Contrast Noise Ratio (CNR), and Measure of Enhancement (EME). Simulation results demonstrate that the proposed particle swarm optimization based contrast enhancement method improves the overall image contrast and enriches the information present in the image. In comparison to other contrast enhancement techniques, the proposed method brings out the hidden details of an image and is more suitable for applications in satellite imaging and night vision.     

A text reading algorithm for natural images

Reading text in natural images has focused again the attention of many researchers during the last few years due to the increasing availability of cheap image-capturing devices in low-cost products like mobile phones. Therefore, as text can be found on any environment, the applicability of text-reading systems is really extensive. For this purpose, we present in this paper a robust method to read text in natural images. It is composed of two main separated stages. Firstly, text is located in the image using a set of simple and fast-to-compute features highly discriminative between character and non-character objects. They are based on geometric and gradient properties. The second part of the system carries out the recognition of the previously detected text. It uses gradient features to recognize single characters and Dynamic Programming (DP) to correct misspelled words. Experimental results obtained with different challenging datasets show that the proposed system exceeds state-of-the-art performance, both in terms of localization and recognition.     

最大差值图决策的低照度图像自适应增强算法

应用于光照分布不均的低照度图像,传统的图像增强算法会出现色彩失真、亮区过度增强等问题,因此提出一种最大差值图决策的低照度图像自适应增强算法。首先,提出最大差值图的概念,通过最大差值图粗略估计出初始光照分量;然后,提出交替引导滤波的算法,利用交替引导滤波对初始光照分量进行校正,实现光照分量的准确估计;最后,设计了图像亮度自适应的伽马变换,能够根据获取的光照分量自适应调整伽马变换参数,从而在增强图像的同时消除光照不均带来的影响。实验结果表明,增强后的图像有效消除了光照分布不均带来的影响,图像亮度、对比度、细节表现能力和色彩保真度都得到了明显提升,平均梯度提升了1倍以上,信息熵提升了14%以上。由于提出的算法对光照分量估计准确,自适应伽马变换针对低照度图像进行了优化,因此,对于夜间等弱光源条件下的彩色图像具有十分有效的增强效果。     

基于纹理复杂度和差分的抗盲检测图像隐写算法

通过分析纹理复杂度对图像隐写分析的影响,提出一种基于纹理复杂度和像素差分的隐写算法。首先,将图像划分为大小相同的分块,通过分块中起点位置的不同计算分块中不同小块的纹理复杂度,选择复杂度最高的图像小块;然后,计算小块的相邻像素差分值,并根据秘密消息的长度和不同方向上的差分值分布确定嵌入阈值,在大于该阈值的差分值中嵌入秘密消息。对多种嵌入算法在不同图像库上做通用盲检测实验,实验结果表明,该算法在抵抗小波高阶统计量分析等盲检测算法能力方面,优于LSB匹配、图像边缘自适应嵌入等隐写算法。     

改进的块差值无损鲁棒图像水印算法

为了解决目前基于块差值无损鲁棒水印算法的不足,提出了一种基于Huffman编码和K-means聚类的改进算法.对嵌入过程中产生的水印负载,利用Huffman编码进一步减少其大小,提高水印嵌入容量;对水印提取过程中,可能发生的1-bit区域和0-bit区域重合的问题,利用K-means聚类算法提高水印提取精确度.实验结果表明,与现有相关算法相比,文种算法在水印嵌入容量和鲁棒性上具有明显优势.     

Deep residual neural network based image enhancement algorithm for low dose CT images

Multimedia Tools and Applications - Current deep learning based image enhancement algorithms attempt to learn the mapping relationship between degraded images and clear images directly. These...     

A rotation- and flip-invariant algorithm for representing spatial continuity information of geographic images in content-based image retrieval

This research proposes a rotation- and flip-invariant algorithm for representing spatial continuity information in high-resolution geographic images for content based image retrieval (CBIR). Starting with variogram concept, the new visual property representation, in the form of a numeric index vector, consists of a set of semi-variances at selected lags and directions, based on three well-justified principles: (1) capture the basic shape of sample variogram, (2) represent the spatial continuity anisotropy, and (3) make the representation rotation- and flip-invariant. The algorithm goes through two tests. The first test confirms that it can indeed align the image representations based on spatial continuity information of objects within images by re-ordering the semi-variances accordingly. In the second test, the algorithm is applied to retrieve seven types of typical geographic entities from an Erie County orthophoto database. The retrieval results demonstrate the effectiveness of the new algorithm in CBIR, as assessed by retrieval precision.     

A total color difference measure for segmentation in color images

A single-value total color difference (TCD) measurement for scene segmentation is proposed and evaluated experimentally. Both chrominance and luminance difference criteria are considered. The luminance component is defined by a unit in luminance change expressed in terms of MacAdam's Just Noticeable Difference, JND. The chromaticity component is derived directly from JND. Experiments using both pixel and region analysis show that the proposed TCD can effectively indicate object boundaries over a wide range of luminance changes. The results have been evaluated both subjectively and quantitatively. For comparison purposes, results have been obtained in several color spaces.     

Digit-serial-in-serial-out systolic multiplier for Montgomery algorithm

This paper proposes a systematic design of a digit-serial-in-serial-out systolic multiplier for the efficient implementation of the Montgomery algorithm in an RSA cryptosystem. For processing speed, the proposed multiplier can also accommodate bit-level pipelining, thereby achieving sample speeds comparable to bit-parallel multipliers with a lower area. If the appropriate digit-size is chosen, the proposed architecture can meet the throughput requirement of a specific application with minimum hardware. The new digit-serial systolic multiplier is highly regular, nearest-neighbor connected, and thus well suited for VLSI implementation.     

A relative difference quotient algorithm for discrete optimization

According to the characteristics of discrete optimization, the concept of a relative difference quotient is proposed, and a highly accurate heuristic algorithm, a relative difference quotient algorithm, is developed for a class of discrete optimization problems with monotonic objective functions and constraint functions. The algorithm starts from the minimum point of the objective function outside the feasible region and advances along the direction of minimum increment of the objective function and maximum decrement of constraint functions to find a better approximate optimum solution. In order to evaluate the performance of the algorithm, a stochastic numerical test and a statistical analysis for the test results are also completed. The algorithm has been successfully applied to the discrete optimization of structures.     

A programmable systolic device for image processing based on mathematical morphology

Systolic array architectures are favourable for special purpose systems as they are simple and offer a high degree of concurrency. A programmable systolic device is designed to cater for all tasks of image processing based on mathematical morphology. The design consists of a systolic memory matrix accessible via a rotation operation by a linear systolic array of simple processing elements. The instruction set consists of 1-bit assignmments, logical and and or and shift operations on the memory. Thus extremely short clock cycles and a high degree of parallelism can be achieved.     

StitchingPHm—A new algorithm for panoramic images

In this paper it is presented a new algorithm for the construction of panoramic images (including 360 panoramas), which has as main characteristic to avoid the distortion that occurs by joining of several successive images in a sequence. We used the SIFT and RANSAC algorithms to find overlap areas between pairs of images, as well as a Blend algorithm for smoothing the joints. As the proposed algorithm doesn’t cause distortions, the subsequent correction is not necessary, contributing to a better performance. The results of experiments using commercial software and also the proposed algorithm were compared through a visual analysis. In addition, a quantitative analysis was done using numeric measures calculated on a panoramic image, generated from an image sequence of a region mapped and georeferenced by Google Earth.