Cubixel: a novel paradigm in image processing using three-dimensional pixel representation

IF 3 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Multimedia Tools and Applications Pub Date : 2024-09-09 DOI:10.1007/s11042-024-20081-6
Sanad Aburass
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Abstract

This paper introduces the innovative concept of the Cubixel—a three-dimensional representation of the traditional pixel—alongside the derived metric, Volume of the Void (VoV), which measures spatial disparities within images. By converting pixels into Cubixels, we can analyze the image’s 3D properties, thereby enriching image processing and computer vision tasks. Utilizing Cubixels, we’ve developed algorithms for advanced image segmentation, edge detection, texture analysis, and feature extraction, yielding a deeper comprehension of image content. Our empirical experimental results on benchmark images and datasets showcase the applicability of these concepts. Further, we discuss future applications of Cubixels and VoV in various domains, particularly in medical imaging, where they have the potential to significantly enhance diagnostic processes. By interpreting images as complex ‘urban landscapes’, we envision a new frontier for deep learning models that simulate and learn from diverse environmental conditions. The integration of Cubixels into deep learning architectures promises to revolutionize the field, providing a pathway towards more intelligent, context-aware artificial intelligence systems. With this groundbreaking work, we aim to inspire future research that will unlock the full potential of image data, transforming both theoretical understanding and practical applications. Our code is available at https://github.com/sanadv/Cubixel.

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立方像素:使用三维像素表示法的新型图像处理范例
本文介绍了立方像素(Cubixel)这一创新概念--传统像素的三维表示法--以及衍生指标--虚空体积(VoV),该指标用于测量图像中的空间差异。通过将像素转换为立方像素,我们可以分析图像的三维属性,从而丰富图像处理和计算机视觉任务。利用立方像素,我们开发出了用于高级图像分割、边缘检测、纹理分析和特征提取的算法,从而更深入地理解了图像内容。我们在基准图像和数据集上的经验性实验结果展示了这些概念的适用性。此外,我们还讨论了 Cubixels 和 VoV 在各个领域的未来应用,特别是在医疗成像领域,它们有可能显著增强诊断过程。通过将图像解释为复杂的 "城市景观",我们为模拟和学习各种环境条件的深度学习模型设想了一个新的领域。将 Cubixels 集成到深度学习架构中有望彻底改变这一领域,为实现更智能、更能感知上下文的人工智能系统提供一条途径。通过这项开创性的工作,我们旨在激励未来的研究,充分释放图像数据的潜力,改变理论理解和实际应用。我们的代码见 https://github.com/sanadv/Cubixel。
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来源期刊
Multimedia Tools and Applications
Multimedia Tools and Applications 工程技术-工程:电子与电气
CiteScore
7.20
自引率
16.70%
发文量
2439
审稿时长
9.2 months
期刊介绍: Multimedia Tools and Applications publishes original research articles on multimedia development and system support tools as well as case studies of multimedia applications. It also features experimental and survey articles. The journal is intended for academics, practitioners, scientists and engineers who are involved in multimedia system research, design and applications. All papers are peer reviewed. Specific areas of interest include: - Multimedia Tools: - Multimedia Applications: - Prototype multimedia systems and platforms
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