An Integrated Image Filter for Enhancing Change Detection Results

07/02/2019
by   Dawei Li, et al.
2

Change detection is a fundamental task in computer vision. Despite significant advances have been made, most of the change detection methods fail to work well in challenging scenes due to ubiquitous noise and interferences. Nowadays, post-processing methods (e.g. MRF, and CRF) aiming to enhance the binary change detection results still fall short of the requirements on universality for distinctive scenes, applicability for different types of detection methods, accuracy, and real-time performance. Inspired by the nature of image filtering, which separates noise from pixel observations and recovers the real structure of patches, we consider utilizing image filters to enhance the detection masks. In this paper, we present an integrated filter which comprises a weighted local guided image filter and a weighted spatiotemporal tree filter. The spatiotemporal tree filter leverages the global spatiotemporal information of adjacent video frames and meanwhile the guided filter carries out local window filtering of pixels, for enhancing the coarse change detection masks. The main contributions are three: (i) the proposed filter can make full use of the information of the same object in consecutive frames to improve its current detection mask by computations on a spatiotemporal minimum spanning tree; (ii) the integrated filter possesses both advantages of local filtering and global filtering; it not only has good edge-preserving property but also can handle heavily textured and colorful foreground regions; and (iii) Unlike some popular enhancement methods (MRF, and CRF) that require either a priori background probabilities or a posteriori foreground probabilities for every pixel to improve the coarse detection masks, our method is a versatile enhancement filter that can be applied after many different types of change detection methods, and is particularly suitable for video sequences.

READ FULL TEXT

page 2

page 4

page 5

page 7

page 8

page 11

page 13

page 14

research
04/20/2022

Image Restoration in Non-Linear Filtering Domain using MDB approach

This paper proposes a new technique based on a non-linear Minmax Detecto...
research
04/27/2012

Background subtraction based on Local Shape

We present a novel approach to background subtraction that is based on t...
research
08/30/2020

How to Design A Generic Accuracy-Enhancing Filter for Discontinuous Galerkin Methods

Higher-order accuracy (order of k+1 in the L^2 norm) is one of the well ...
research
06/02/2021

Unsharp Mask Guided Filtering

The goal of this paper is guided image filtering, which emphasizes the i...
research
05/16/2019

Inductive Guided Filter: Real-time Deep Image Matting with Weakly Annotated Masks on Mobile Devices

Recently, significant progress has been achieved in deep image matting. ...
research
03/31/2020

DeepLPF: Deep Local Parametric Filters for Image Enhancement

Digital artists often improve the aesthetic quality of digital photograp...
research
04/16/2018

Comparative study of motion detection methods for video surveillance systems

The objective of this study is to compare several change detection metho...

Please sign up or login with your details

Forgot password? Click here to reset