A wavelet transform based POCS Superresolution algorithm

Research interest in multi-frame Superresolution has risen substantially in recent years.This paper presents a modified Projection Onto Convex Set (POCS) superresolution method based on wavelet transform.The method analyzes the image formation model from wavelet multiresolution analysis point of view and defines an closed convex set and its corresponding projection based on wavelet transform.An iterative procedure is utilized to reduce the estimated errors of the result image,and this guarantees the estimated image to lay in the intersection of different convex sets,thus produces a high resolution image with a reduced error.The effectiveness of the algorithm is demonstrated by experimental results.     

基于正则化处理的超分辨率重建

针对超分辨率重建的病态反问题进行研究。该文首先介绍超分辨率重建的数学模型,分析了最小二乘估计及其病态性。其次给出病态问题的正则化泛函,并提出一种自适应动态确定正则化系数的方法,主要研究了迭代算法的收敛性和参数选择等问题。实验结果验证了方法的有效性。     

Phase-driven spatially variant regularization for image resolution enhancement

A phase-driven spatially variant regularization approach is proposed in this letter to perform image resolution enhancement. The proposed approach adaptively adjusts the degree of regularization using the phase coherence measure of the local content of the image. This is in contrast to that a spatially invariant regularization parameter is exploited for the whole image in conventional approaches. Experiments are conducted to demonstrate the superior performance of the proposed approach.     

物理逆问题中的一个定理

本文将物象重建归结为描述这一物理过程的积分方程的定义域的反演问题。本文提出了一个定理,当被积函数满足某些先决条件时,则该定义域的轮廓可以借助于这个定理反演获得。计算机模拟结果表明了本文的论述和定理的正确性。     

正交化超分辨算法的误差灵敏度分析

本文给出了基于Gram-Schmidt正交化方法的超分辨算法,并分析了该算法对阵列幅度和相位误差的灵敏度.给出了两个目标、不同阵元数和不同阵元间距等情况下的灵敏度计算结果。结果表明,本文的算法在目标小角度间隔、大阵元数的情况下,受幅相误差的影响没有最大似然估计(MLM)和MUSIC算法敏感。     

Plane surface detection and reconstruction using segment-based tensor voting

A Segment-based Tensor Voting (SBTV) algorithm is presented for planar surface detection and reconstruction of man-made objects. Our work is inspired by piecewise planar stereo reconstruction. During the vital procedure to detect and label the planar surface, the two main contributions are: first, tensor voting is used for obtaining the geometry attribute of the 3D points cloud. The candidate planar patches are generated through scene image segment of low variation of color and intensity. Second, we over-segment the scene image into the segment and the candidate 3D planar patch is generated. The SBTV algorithm is used on 3D points cloud sets to identify the co-plane on the candidate patch. After detecting every planar patch, the geometry architecture of object is obtained. The experiments demonstrate the effectiveness of our proposed approach on either outdoor or indoor datasets.     

最大熵线性预测超分辨算法的误差灵敏度分析

本文分析了Burg提出的最大熵线性预测超分辨算法对阵列幅度和相位误差的灵敏度。给出了具有两个目标、不同阵元数和不同间距等情况下的数值计算结果。结果表明最大熵算法较最大似然估计(MLM)算法和MUSIC算法对幅相误差的影响更加敏感。文中还给出了最大熵算法和MUSIC算法分辨目标的实验结果。     

基于最大似然法的超分辨率离散谱估计算法

基于最大似然法的交替陷波周期图算法（ＡＮＰＡ）是一种超分辨率的谱估计算法,它同时具有超分辨率、高精度和低信噪比门限的特性。本文提出了一种计算陷波周期图的新算法,它可使运算量和存储容量大幅度下降。计算机仿真结果证明了这种算法在分辨能力和估计精度方面优于己有算法。     

基于L曲线的自适应时空正则化视频超分辨率重建

为了解决视频超分辨率重建的病态问题,以得到良好的重建效果,提出了一种新颖的视频超分辨率重建算法。在算法中引入了时空联合正则化算子,通过视频帧本身的空间平滑信息和视频相邻帧的帧间相关先验信息的引入,提高了解的质量;同时,为了选择合适的时空正则化系数,提出了基于L曲线的自适应时空正则化系数计算方法,可以自适应地计算合适的正则化系数。通过对模拟图像序列和真实视频序列的实验结果表明,算法能得到较为精确的解,重建出具有良好视觉效果的高分辨率视频。     

基于连续插值逼近的电阻抗成象的图象ANIL建算法

本文提出了电阻抗成象的图象重建算法中一种新的电导率分布函数逼近方法连续插值函数逼近法.它充分利用有限元方法计算上的特点,在计算量不增加甚至有所减少的情况下,获得了比传统的分片常数逼近法更好的图象重建效果.     

EIGNVALUE SHIFT SUPPERRESOLUTION ALGORITHM

This paper provides a new approach to spatial spectral estimation, called eigenvalue shift superresolution algorithm. This method avoids the inverse covariance matrix. It can be applied to the processing of data received by spatially distributed array of sensors.     

A image-upscaling engine for 1080p to 4k using gradient-based interpolation

ABSTRACT

Image upscaling is an efficient solution to eliminate the gap between image/video sizes and display resolutions. Generally, image-upscaling algorithms use computation-intensive edge detection and filtering to improve their performance with inefficient hardware performances. In this study, an image-upscaling algorithm for 1080p to 4K using gradient-based interpolation technique is proposed. It simply adopts the horizontal and vertical gradients among source pixels to consider the texture content among them. This technique inherits the textures from source pixels and further extends them to target pixels using spatial-correlation. Experiment results demonstrate that this study has better average peak-to-noise-ratio (PSNR) and structural similarity (SSIM). The hardware architecture is realised using TSMC CMOS 0.18 μm technology. It comprises two core techniques: bubble-eliminating data scheduling (BEDS) and memory-efficient gradient generator (MEGG). BEDS can efficiently remove bubble cycles to improve hardware performances. MEGG can use compact memory capacity to produce gradient information. Its working frequency is 178 MHz with a power consumption of 9.43 mW. The maximum throughput is as high as 712 Mpixels/sec, which can sufficiently support 4K@60 fps. This study presents higher hardware efficiencies with better visual quality and object completeness in image upscaling for 1080p to 4K applications.     

Digital reconstruction of images from their projections in polar coordinates

In a wide variety of applications, it is necessary to infer the structure of a three-dimensional object from its projections. Usually, the problem is reduced to the reconstruction of a series of two-dimensional (planar) sections from a set of one-dimensional (linear) projections. In this paper, starting from a polar representation of the density function, we present some closed form formulas, which can be successfully used in the reconstruction of images. The results of some numerical tests are also presented.     

特征值平移超分辨率算法

本文分析了逆幂迭代算法的收敛速度。为了克服逆幂迭代算法矩阵求逆的过程,提出了特征值平移幂迭代算法,并分析了它的收敛速度,给出了计算机模拟结果。     

基于梯度转向核的半随机傅里叶域压缩重构算法

针对压缩遥感过程中非严格稀疏和傅里叶域欠采样噪声导致的伪影和混叠现象,本文提出了基于梯度转向核的压缩重构策略（GradSK）。在压缩感知编码过程中提出了半随机傅里叶测量的方式,既保留图像的概要分量,同时保证了K-空间随机欠采样的非连贯性。在压缩感知解码过程中提出了由基于多阶梯度的转向核与有限差分总方差（TV）结合的方法,来解决解码过程中的无约束凸框架问题。实验表明,该方法在解决无噪采样和有噪采样的过程中均有较好性能。     

模糊多准则核磁共振图象重建技术

本文提出一种适合核磁共振频谱数据成象的多准则优化成象算法，我们根据数字图象品质价价的模糊性，从模糊数字理论出发，提出一套模糊指数函数，而这些准则函数，经过一系列数学处理，可以把空间域的多准则的问题转化为频域处理，从而推出一种快速，有效的成象算法。     

Efficient reconstruction of compressively sensed images and videos using non-iterative method

Compressed sensing is widely applied for compression and reconstruction of images and videos by projecting the pixel values to smaller dimensional measurements. These measurements are reconstructed at the receiver using various reconstruction procedures. Greedy algorithms are often used for such recovery. These solve the least squares problem to find the best match with minimum error. This is a time consuming and complex process, giving rise to a trade-off between reconstruction performance and algorithmic performance. This work proposes a non-iterative method, viz., non-iterative pseudo inverse based recovery algorithm (NIPIRA), for reconstruction of compressively sensed images and videos with small complexity and time consumption, provided the reconstruction quality is maintained. NIPIRA gives a minimum PSNR of 32 dB for very few measurements (M/N = 0.3125) and accuracy of above 97%. There is more than 92% of decrease in elapsed time compared with other iterative algorithms. NIPIRA is tested for its performance with respect to many other objective measures as well. The complexity of NIPIRA is s times less than existing recovery algorithms.     

A nonconvex nonsmooth regularization method with structure tensor total variation

In this paper, a novel regularization method for image restoration and reconstruction is introduced which is accomplished by adopting a nonconvex nonsmooth penalty that depends on the eigenvalues of structure tensor of the underlying image. At first, an alternating minimization scheme is developed in which the problem can be decomposed into three subproblems, two of them are convex and the remaining one is smooth. Then, the convergence of the sequence which generate by the alternating minimization algorithm is proved. Finally, the efficient performance of the proposed method is demonstrated through experimental results for both grayscale and vector-value images.     

Super resolution image reconstruction through bregman iteration using morphologic regularization

Multiscale morphological operators are studied extensively in the literature for image processing and feature extraction purposes. In this paper, we model a nonlinear regularization method based on multiscale morphology for edge-preserving super resolution (SR) image reconstruction. We formulate SR image reconstruction as a deblurring problem and then solve the inverse problem using Bregman iterations. The proposed algorithm can suppress inherent noise generated during low-resolution image formation as well as during SR image estimation efficiently. Experimental results show the effectiveness of the proposed regularization and reconstruction method for SR image.