Data hiding during image processing using capsule networks

Abstract

In daily life, some conventional image processing operations, e.g., histogram equalization, and filtering, are widely used to improve the visual quality of digital images. This paper designs an image processing network based on CapsNets (capsule networks), in which additional data can be carried in the processed image. Given an image to be processed, the proposed network is able to achieve some conventional image processing operations with satisfactory results. Meanwhile, additional data can be embedded into the processed image during the process of training, and the existence of additional data cannot be discovered. In this way, additional data can be transmitted secretly via the processed image, which looks normal. Compared with existing data hiding algorithms that embed data by modifying image content, the proposal to embed data during the process of training is more secure. Experimental results verify the effectiveness of the proposed network, including the quality of the processed image, embedding capacity, and security.