Single Image Reflection removal Using Feature Difference Enhancement

Abstract

Most existing reflection removal methods pay too much attention to the transmission layer and ignore the mutual complementary mechanisms between the transmission layer and the reflection layer. To make full use of the complementarity and distinction between the reflection and transmission layers in reflection-contaminated images, we propose a novel single image reflection removal framework using the feature difference and adaptive information exchange between the transmission and reflection layers of reflection-contaminated images. First, we design a feature difference enhancement module to distinguish and enhance the feature difference of the reflective and transmissive layers. Second, we propose an adaptive information exchange module between transmission and reflection layers in the decoder, which can capture more complementary information. Finally, we introduce a 1/4 selective Instance Normalization strategy to improve our reflection removal tasks further. The experimental results demonstrate the efficiency of the proposed method and superior performance against state-of-the-art methods.