Local disparity remapping to enhance depth quality of stereoscopic 3D images using stereoacuity function

Abstract

This paper proposes a simple but effective method for local disparity remapping that is capable of enhancing the depth quality of stereoscopic 3D images. In order to identify and scale the unperceivable difference in disparities in a scene, the proposed approach decomposes the disparity map into a two disparity layers: one is the coarse disparity layer that contains the information of the global depth structures and the other is the detail disparity layer that contains the details of the depth structures. Then, the proposed method adaptively manipulates the detail disparity layer in depth and image spaces under the guidance of a stereoacuity function, which describes the minimum amount of perceivable disparity difference given a disparity magnitude. In this way, relative depths between objects (or regions) can be effectively emphasized while providing a spatial adaptability in the image space. Experimental results showed that the proposed method was capable of improving the depth quality and overall viewing quality of stereoscopic 3D images as well.