基于动态卷积和视觉曼巴的图像压缩模型

IF 2 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

IET Image Processing Pub Date : 2025-04-17 DOI:10.1049/ipr2.70080

Lingchen Qiu, Enjian Bai, Yun Wu, Yuwen Cao, Xue-qin Jiang

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引用次数: 0

摘要

我们提出了一种利用视觉曼巴和动态卷积的有效图像压缩方案，解决了现有方法的局限性，例如无法捕获远程像素依赖性和高计算复杂性。我们的方法改进了全局和局部信息学习，减少了计算成本。在Kodak， Tecnick和CLIC数据集上的实验结果表明，我们的模型以较低的算法复杂度获得了具有竞争力的性能。我们的代码可以在https://github.com/Lynxsx/ICVM上找到。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Image Compression Model Based on Dynamic Convolution and Vision Mamba

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Image Compression Model Based on Dynamic Convolution and Vision Mamba

We propose an efficient image compression scheme leveraging Vision Mamba and dynamic convolution, addressing the limitations of existing methods, such as failure to capture long-range pixel dependencies and high computational complexity. Our approach improves both global and local information learning with reduced computational cost. Experimental results on the Kodak, Tecnick and CLIC datasets show that our model achieves competitive performance with lower algorithm complexity. Our code is available on: https://github.com/Lynxsx/ICVM.

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来源期刊

IET Image Processing 工程技术-工程：电子与电气

CiteScore

5.40

自引率

8.70%

发文量

282

审稿时长

6 months

期刊介绍： The IET Image Processing journal encompasses research areas related to the generation, processing and communication of visual information. The focus of the journal is the coverage of the latest research results in image and video processing, including image generation and display, enhancement and restoration, segmentation, colour and texture analysis, coding and communication, implementations and architectures as well as innovative applications. Principal topics include: Generation and Display - Imaging sensors and acquisition systems, illumination, sampling and scanning, quantization, colour reproduction, image rendering, display and printing systems, evaluation of image quality. Processing and Analysis - Image enhancement, restoration, segmentation, registration, multispectral, colour and texture processing, multiresolution processing and wavelets, morphological operations, stereoscopic and 3-D processing, motion detection and estimation, video and image sequence processing. Implementations and Architectures - Image and video processing hardware and software, design and construction, architectures and software, neural, adaptive, and fuzzy processing. Coding and Transmission - Image and video compression and coding, compression standards, noise modelling, visual information networks, streamed video. Retrieval and Multimedia - Storage of images and video, database design, image retrieval, video annotation and editing, mixed media incorporating visual information, multimedia systems and applications, image and video watermarking, steganography. Applications - Innovative application of image and video processing technologies to any field, including life sciences, earth sciences, astronomy, document processing and security. Current Special Issue Call for Papers: Evolutionary Computation for Image Processing - https://digital-library.theiet.org/files/IET_IPR_CFP_EC.pdf AI-Powered 3D Vision - https://digital-library.theiet.org/files/IET_IPR_CFP_AIPV.pdf Multidisciplinary advancement of Imaging Technologies: From Medical Diagnostics and Genomics to Cognitive Machine Vision, and Artificial Intelligence - https://digital-library.theiet.org/files/IET_IPR_CFP_IST.pdf Deep Learning for 3D Reconstruction - https://digital-library.theiet.org/files/IET_IPR_CFP_DLR.pdf