数字图像处理及其技术文献综述

Abhishek A. Vernekar, Subramanya Bhat
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引用次数: 0

摘要

目的:了解数字图像处理领域的知识现状。确定以往研究中探索过的关键概念、理论和方法。探索数字图像处理中使用的各种技术和算法。评估现有方法的优缺点。找出当前技术的差距或局限性。通过总结和归纳相关研究,提供研究背景。说明不同的研究如何促进对数字图像处理的整体理解。找出您的研究可以解决的现有文献中的空白。确定需要进一步研究的领域。为在现有文献背景下讨论和解释您的研究成果奠定基础。使您能够将研究结果与更广泛的数字图像处理领域联系起来:明确界定文献综述的范围(如具体技术、应用或时期)。说明文献综述的目标,如确定趋势、评估方法或解决研究空白。制定全面的搜索策略,以确定相关文献。利用学术数据库、期刊、会议和其他知名来源。结合使用关键词、布尔运算符和控制词汇(如 MeSH 术语)来完善搜索查询。根据既定标准系统地审查和选择相关文献。记录整个过程,包括搜索的数据库、使用的关键词以及纳入/排除的原因。找出现有文献中的不足,并提出未来研究的潜在途径。讨论这些差距对该领域知识进步的影响:文献经常讨论各种图像增强技术,如直方图均衡化、对比度拉伸和空间过滤。研究人员探讨了这些技术在不同应用中提高图像质量的有效性。经常讨论的分割方法包括阈值分割、基于区域的分割和聚类算法。使用纹理、颜色和形状等特征的物体识别和分类技术也是常见的话题。不同的图像压缩算法,如 JPEG、JPEG2000 和各种基于小波的方法,经常在压缩比和质量方面进行比较。文献可能涉及实时图像处理挑战和解决方案,特别是在视频监控、自动驾驶汽车和增强现实等应用中:确保文献综述全面涵盖数字图像处理领域的关键和最新作品。这包括基础理论、算法和应用。确定开创性论文、具有里程碑意义的研究和最新进展,以创建该领域的发展时间表:现有文献综述
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Literature Review on Digital Image Processing and Its Techniques
Purpose: Understand the current state of knowledge in the field of digital image processing. Identify key concepts, theories, and methodologies that have been explored in previous research. Explore the various techniques and algorithms used in digital image processing. Evaluate the strengths and weaknesses of existing methods. Identify gaps or limitations in current techniques. Provide a context for the research by summarizing and synthesizing relevant studies. Show how different studies contribute to the overall understanding of digital image processing. Identify gaps in the existing literature that your research can address. Determine areas where further investigation is needed. Offer a foundation for discussion and interpretation of your results in the context of existing literature. Enable you to relate your findings to the broader field of digital image processing. Design/Methodology/Approach: Clearly define the scope of your literature review (e.g., specific techniques, applications, or periods). State the objectives of the literature review, such as identifying trends, evaluating methodologies, or addressing research gaps. Develop a comprehensive search strategy to identify relevant literature. Utilize academic databases, journals, conferences, and other reputable sources. Use a combination of keywords, Boolean operators, and controlled vocabulary (e.g., MeSH terms) to refine search queries. Systematically review and select relevant literature based on the established criteria. Document the process, including databases searched, keywords used, and reasons for inclusion/exclusion. Identify gaps in the existing literature and propose potential avenues for future research. Discuss the implications of these gaps for the advancement of knowledge in the field Findings/Results: Literature often discusses various image enhancement techniques such as histogram equalization, contrast stretching, and spatial filtering. Researchers explore the effectiveness of these techniques in improving image quality for different applications. Segmentation methods, including thresholding, region-based segmentation, and clustering algorithms, are frequently discussed. Object recognition and classification techniques using features like texture, color, and shape are common topics. Different image compression algorithms, such as JPEG, JPEG2000, and various wavelet-based methods, are often compared in terms of compression ratio and quality. The literature might address real-time image processing challenges and solutions, especially in applications like video surveillance, autonomous vehicles, and augmented reality. Originality/Value: Ensure that the literature review comprehensively covers key and recent works in digital image processing. This includes foundational theories, algorithms, and applications. Identify seminal papers, landmark studies, and recent advancements to create a timeline of the field's development. Paper Type: Review of existing literature
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