Enhanced resampling detection based on image correlation of 3D stereoscopic images

Abstract

In this paper, we propose a resampling detection method for stereoscopic images. Although previous resampling techniques can be applied to stereoscopic images, performance improvement is hard to be expected with the two separated results. In this research, we found a strong relationship between the left and right images derived from the characteristics of the stereoscopic images. The proposed technique exploits that relationship of the stereoscopic images as additional information for reliable detection performance. Furthermore, the proposed method includes a preprocessing step to acquire the independent performance from the image's own characteristics. The experimental results exhibit superior performance compared with the existing works.

Camera Identification of DIBR-based Stereoscopic Image using Sensor Pattern Noise

“…이는 사람의 단안에서 공간감을 [4,5] , DIBR 영상판별 [6,7] , 재표본화 탐지 [8] 카메라 판별에는 렌즈 수차 [9] , 색 수차 [10] , CFA(Color Filter Array) 보간법 [11] , 화소 결함패턴 [12] , SPN(Sensor Pattern Noise) [13] , 양자화 테이블 [14] 깊이영상 기반으로 중앙영상의 화소마다 식 (1)의 워핑(Warping)을 적용하여, 좌/우 영상을 생성한다 [15] . [16] , 수평 보간법 [17] , 외삽법 [18] , 모드선택 [19] 등 다양한 방법들이 있다.…”