Small Target Detection Using Bilateral Filter Based on Edge Component

Abstract

Bilateral filter (BF) performs sharpness enhancement and noise removal by using two Gaussian filters, the domain filter in spatial domain and the range filter in intensity domain. To apply the BF to infrared (IR) small target detection, the standard deviation of the two Gaussian filters need to be changed adaptively between the background region and the target region. This paper presents a new BF for small target detection with the adaptive standard deviation based on the analysis of the edge component, also having the variable filter size. At first, threshold of pixel edge components for four directions decides whether any pixel is potential small targets or not. For the proposed BF operation for the potential small target pixels, its edge component is mapped to two standard deviations of the domain filter and the range filter in the proposed BF by mapping function. When the BF comes to a target region, the two standard deviations increase in proportion to the edge component to blur the small targets. To further blur the small targets, the filter size of the BF also increases by its edge component. This enables the BF to perform better and become more suitable in the field of small target detection Experimental results demonstrate that the proposed method is more robust and efficient than the conventional methods.

Small target detection using bilateral filter and temporal cross product in infrared images

“…Bae et al proposed the BF based on the sum of the first derivative of four directions in local region [9]. And then the standard deviation of BF is controlled using its value.…”

“…Furthermore, aero-optic disturbances and air turbulence make the SNR of a single IR image very low (SNR < 3) in the real environments. Recently, many researchers have developed several spatial or temporal algorithms for the detection of moving targets in IR image sequences [4][5][6][7][8][9]. The spatial processing methods utilize the assumption that the target has a brighter intensity than the background, due to higher temperatures.…”

“…Though this method can detect the exact target trajectory, it still has a high false alarm rate. Bae et al proposed the bilateral filter (BF) based on the edge component for small target detection [9]. In this method, BF is operated as the background predictor by blurring the target through the increase of standard deviation in target region.…”

Background Suppression for Infrared Dim and Small Target Detection Using Local Gradient Weighted Filtering

“…Spatial filter-based methods utilize the grey level of target and background in the image to predict the background. Typical spatial methods include max-mean/median filter [5] , top-hat [6] , two-dimensional minimum mean square error (TDLMS) [7] , bilateral filter [8] , etc. This kind of method has the advantages of simple principle and easy realization, but it is not effective in IR images with low contrast and heavy clutter background.…”

Infrared Target Extraction Using Weighted Information Entropy and Adaptive Opening Filter

“…Since the development of IR-guided missiles, various IR small target detection methods, such as the spatial filter-based method [8]- [10], morphology-based method [11], and temporal-based method [12]- [13] In IR images, objects with different IR radiation normally appear in the form of different changes in gray values. To describe the change in gray values on different objects more clearly, the concept of a "complex degree" was presented [14]- [15].…”