To optimize the visual effects of digital media images,this article introduces an innovative image optimization strategy that relies on a multi-scale adaptive attention mechanism.This method achieves precise capture and efficient integration of multi-dimensional features of images by constructing a unique network architecture,effectively reducing the repetition of content and improving the efficiency and quality of image processing.The article uses Laplace operator to accurately identify missing information in images and designs an efficient loss function to comprehensively compensate for information loss during the processing,thereby significantly improving the overall quality of the image.The experimental results show that the image enhanced by this method achieves over 0.9 on a comprehensive quality evaluation index in terms of color,brightness,and saturation,and also exceeds 0.85 in terms of structural similarity index,which fully verifies the outstanding performance of this method in the field of image enhancement.
关键词
多尺度自适应注意力/数字媒体图像/图像增强/拉普拉斯算子/损失函数
Key words
multi-scale adaptive attention/digital media image/image enhancement/Laplacian operator/loss function
维普
万方数据