图像压缩中运动估计的符合启发式算法

IF 4.6 2区 数学 Q1 MATHEMATICS, APPLIED
Fernando José Hernández Gómez
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引用次数: 0

摘要

np完备性理论指出,对于这类np困难问题,不可能存在精确和有效的算法。处理NP困难的一种方法是放宽最优性要求,转而寻找接近最优的解。这是近似算法背后的主要思想,它被称为启发式或元启发式。运动估计问题是一个计算复杂度很高的过程,它需要足够的内存空间和执行时间。它代表了静态、动态和视频图像序列编码的成本。主要任务是尽量减少失真率,提高视觉质量。这使得编码、图像压缩和视频领域的研究集中在寻找有效的算法来在合理的时间内对运动进行估计。如果分析一个包含n个元素的图像列表,则存在可行解。因此,穷举搜索太慢了,即使对于解空间的小值也是如此。因此,从实际的角度来看,具有高效和快速的启发式算法,避免彻底搜索是至关重要的。在本研究中,我们设计并实现了基于频域的启发式算法,该算法应用于余弦和小波的离散变换系数。此外,我们还提出了时域算法,如块匹配算法,该算法将搜索重点放在当前图像与参考图像的最大重合上。本研究工作中使用的算法是用数学编程语言MATLAB编写的。此外,我们回顾了常用的图像处理、视频、压缩算法和运动估计的基本概念。算法的评估是用一组由以前的采集系统提供的图像进行的。我们展示了视觉质量的改进,压缩或重构信息的数量以及在搜索像素或图像之间的相似性时方法的行为。最后,我们促进传播新的科学研究路线,从而扩大和改进研究,产生新知识,因为这是尼加拉瓜教育学科中的一个年轻领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Heuristic Algorithms of Coincidence for the Estimation of Movements in Compression of Images
The NP-Completeness theory states that exact and efficient algorithms are unlikely to exist for the class of NP-difficult problems. One way to deal with NP hardness is to relax the optimality requirement and look for solutions instead that are close to the optimum. This is the main idea behind the approximation algorithms, which are called heuristic or metaheuristic. The problem of motion estimation is a process with a high degree of computational complexity, it requires sufficient memory space and execution time. It represents the cost of static, dynamic and video image sequence coding. The main task is to minimize the distortion rate and improve visual quality. This makes research in the field of coding, image compression and video focus on finding efficient algorithms to carry out the estimation of movement in a reasonable time. If a list of images of n elements is analyzed, there are feasible solutions. So, an exhaustive search is too slow, even for small values of the solution space. Therefore, from a practical point of view, it is crucial to have efficient and fast heuristic algorithms that avoid thorough search. In this investigation we design and implement heuristic algorithms, based on the frequency domain, which are applied on the coefficients of the discrete transform of the cosine and wavelets. Also, we propose temporal domain algorithms such as block-matching algorithms, which focus your search on the maximum coincidence of the current image with the reference one. The algorithms used during the implementation of this research work were written with the mathematical programming language MATLAB. In addition, we review the basic concepts of image processing, video, compression algorithms and motion estimation frequently used. The evaluation of the algorithms was carried out with a set of images provided by a previous acquisition system. We show the improvement of visual quality, the amount of compressed or reconstructed information and the behavior of the methods in the search for similarities between pixels or images. Finally, we contribute to the dissemination of new lines of scientific research that lead to the expansion and improvement of the study, the generation of new knowledge, since it is a young area within the Education discipline of Nicaragua.
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来源期刊
CiteScore
8.80
自引率
5.00%
发文量
18
审稿时长
6 months
期刊介绍: Applied and Computational Mathematics (ISSN Online: 2328-5613, ISSN Print: 2328-5605) is a prestigious journal that focuses on the field of applied and computational mathematics. It is driven by the computational revolution and places a strong emphasis on innovative applied mathematics with potential for real-world applicability and practicality. The journal caters to a broad audience of applied mathematicians and scientists who are interested in the advancement of mathematical principles and practical aspects of computational mathematics. Researchers from various disciplines can benefit from the diverse range of topics covered in ACM. To ensure the publication of high-quality content, all research articles undergo a rigorous peer review process. This process includes an initial screening by the editors and anonymous evaluation by expert reviewers. This guarantees that only the most valuable and accurate research is published in ACM.
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