Quaternionic extended local binary pattern with adaptive structural pyramid pooling for color image representation

Abstract

This paper proposes a novel feature representation method for color images, namely quaternionic extended local binary pattern (QxLBP) with adaptive structural pyramid pooling (ASPP). First, we propose a QxLBP operator to encode local neighboring information and complementary modulus and phase information in the quaternion domain of color images. In QxLBP, an extended quaternionic representation (EQR) is proposed which introduces an information term into the real part of a quaternion. The resulting EQR enables us to flexibly encode discriminative features and handle multichannel image data. Second, we propose ASPP as a multiresolution pooling way to aggregate local features. Unlike the traditional spatial pyramid pooling which is sensitive to image rotation and spatial changes, ASPP is structure-oriented pooling which can adaptively aggregate the encoded features into multiresolution histogram representations. Experiments on four benchmark image datasets demonstrate that the proposed method achieves the state-of-the-art performance for color texture classification and scene categorization.