A novel noise filter based on interesting pattern mining for bag-of-features images

•We first propose to utilize the cosine interesting pattern to construct the noise filter.•We then prove that to filter noise only requires to mine the shortest cosine interesting patterns, which dramatically simplifies the mining process.•We present an in-breadth pruning technique to further speed up the mining process.

Improving the quality of image data through noise filtering has gained more attention for a long time. To date, many studies have been devoted to filter the noise inside the image, while few of them focus on filtering the instance-level noise among normal images. In this paper, aiming at providing a noise filter for bag-of-features images, (1) we first propose to utilize the cosine interesting pattern to construct the noise filter; (2) then we prove that to filter noise only requires to mine the shortest cosine interesting patterns, which dramatically simplifies the mining process; (3) we present an in-breadth pruning technique to further speed up the mining process. Experimental results on two real-life image datasets demonstrate effectiveness and efficiency of our noise filtering method.