Inverse texture synthesis in wavelet packet trees

Abstract

Inverse texture synthesis (ITS) plays an important role in many computer vision applications. It aims at generating small compaction images to capture significant features of textures, from which arbitrarily large images with similar textures can be re‐synthesised. This study presents a fast approach to ITS with two algorithms developed in hierarchical wavelet packet (WP) trees: the modified inverse texture synthesis (MITS) algorithm, which extends the ITS algorithm into the WP domain, and the wavelet‐packet‐tree‐based cropping (WPTC) algorithm for the initialisation of MITS. Experimental results show that the combination of WPTC and MITS termed the image compaction in wavelet packet trees algorithm outperforms the ITS algorithm in terms of the ‘peak signal‐to‐noise ratio’ and computation time.

Warp-knitted fabric defect segmentation based on the non-subsampled wavelet-packet-based Contourlet transform

“…Furthermore, in the decomposition of the wavelet-packet transform, the best tree selection 22 and sub-bands de-noising should be taken into account. Although wavelet-packet transform is more flexible than wavelet transform, the calculated amount of it is larger.…”