Image enhancement methods in digital media with multi-scale adaptive attention
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.
multi-scale adaptive attentiondigital media imageimage enhancementLaplacian operatorloss function
万方数据
维普
