基于深度学习的数字图像处理实验平台开发

Development of Modern Digital Image Processing Experiment Platform Based on Deep Learning

摘要:

数字图像处理实验平台在工业、医学、农业等领域具有重要意义,可以为图像处理任务提供高效、准确的解决方案。为解决数字图像处理中存在的信息缺失、噪声干扰、低分辨率等问题，通过结合卷积神经网络和生成对抗网络等先进技术，采用模块化设计及数据增强、迁移等方法，设计了一种多功能的数字图像处理平台，包括图像超分辨率重建、风格转换、去噪、去雾、修复、抠图等功能。用户可以根据需求选择不同的处理模块构建自己的处理系统，体现了平台的灵活性和可定制性。通过案例验证，证实了该图像处理实验平台的有效性和便捷性。

Abstract:

Digital image processing experimental platform is of great significance in industry, medicine, agriculture and other fields, and can provide efficient and accurate solutions for image processing tasks. In order to solve the problems of information loss, noise interference and low resolution in digital image processing, a multi-functional digital image processing platform is successfully designed by combining advanced technologies such as convolutional neural network and generative adversarial network, and adopting the methods of modular design, data enhancement and migration. Including image super resolution reconstruction, style conversion, noise removal, fog removal, repair, matting and other functions. Users can choose different processing modules according to their needs to build their own processing system, showing the flexibility and customizability of the platform. The effectiveness and convenience of the image processing experimental platform are verified by a case study.