Bilateral filter

About: Bilateral filter is a research topic. Over the lifetime, 3500 publications have been published within this topic receiving 75582 citations.

Hybrid Speckle Noise Reduction Method for Abdominal Circumference Segmentation of Fetal Ultrasound Images

Abstract: Fetal biometric size such as abdominal circumference (AC) is used to predict fetal weight or gestational age in ultrasound images. The automatic biometric measurement can improve efficiency in the ultrasonography examination workflow. The unclear boundaries of the abdomen image and the speckle noise presence are the challenges for the automated AC measurement techniques. The main problem to improve the accuracy of the automatic AC segmentation is how to remove noise while retaining the boundary features of objects. In this paper, we proposed a hybrid ultrasound image denoising framework which was a combination of spatial-based filtering method and multiresolution based method. In this technique, an ultrasound image was decomposed into subbands using wavelet transform. A thresholding technique and the anisotropic diffusion method were applied to the detail subbands, at the same time the bilateral filtering modified the approximation subband. The proposed denoising approach had the best performance in the edge preservation level and could improve the accuracy of the abdominal circumference segmentation.

Accelerate bilateral filter using Hermite polynomials

Abstract: The bilateral filter (BF) as an edge-preserving lowpass filter is a valuable tool in various image processing tasks, including noise reduction and dynamic range compression. However, its computational cost is too high to apply in the real-time processing tasks as the range kernel, which acts on the pixel intensities, making the averaging process nonlinear and computationally intensive, particularly when the spatial filter is large. Using the well-known Hermite polynomials, a BF accelerating method is proposed, which reduces the computational complexity from O(r(2)n) to O(n), where r denotes the filter size of a BF and n is the total number of pixels in an image.

Iterative range-domain weighted filter for structural preserving image smoothing and de-noising

Abstract: The filtering weights from both spatial domain and range domain in the bilateral filtering always restrict filtering output value highly related to very close neighboring pixels, which results in very small changes before and after filtering. In order to better resolve the problem of piece-wise smoothness image’s de-noising, such as artifact removal of compressed depth image, we firstly propose an iterative range-domain weighted filter method. The filtering weights of the proposed method are calculated within a fixed window in an iterative way according to both pixel similarity in the range domain and image’s pixel occurring frequency, but there is no filtering weight from the spatial domain. Secondly, the proposed method is combined with Gaussian filtering as an engine in order to finish the task of image smoothing, because image smoothing for extracting structures is often sensitive to image’s fine details with strong gradients during suppressing image’s textures. To demonstrate the efficiency, we have applied the proposed method into many applications. For example, the proposed method has better performances on compressed depth artifact removal than BF, CVBF, and ADTF. Meanwhile, the proposed method is used for capture-noise removal of depth image. Additionally, the proposed method performs better performance on structural information preservation for image smoothing, as compared to several existing methods.

Robust Nighttime Road Lane Line Detection using Bilateral Filter and SAGC under Challenging Conditions

Abstract: In the last two decades, Advanced Driver Assistance Systems (ADAS) has been one of the most actively conducted areas of studies for reducing traffic accidents. Road lane line detection is one of the essential modules of ADAS. Lots of advancement has been already done, but most of the recent papers did not consider the wide variability of challenging nighttime conditions. In this paper, a method to detect nighttime lane line under different challenging conditions proposed. This simple technique can reach the real-time computation for ADAS applications and at the same time, can handle multiple challenges at a time. In the beginning, Bilateral Filter has been used to reduce the noise while preserving the edges. Next, we choose an optimized threshold (OT) for the Canny edge detector, which can detect edges under a wide variability of nighttime illumination conditions. After that Region of Interest (ROI) is selected using an equilateral triangle-shaped mask which helps to reduce computation time and remove unwanted edges. After that, lines are extracted by Probabilistic Hough Transform (PHT). Finally, a robust technique Slope and Angle based Geometric Constraints (SAGC) is proposed to remove the non-lane lines extracted by PHT. SAGC reduce false detection significantly. Experimental results show that the average detection rate is 94.05%, and the average detection time is 26.11ms per frame which outperformed state-of-the-art method.

Automatic correction of amateur photos damaged by backlighting

Abstract: In this paper we consider a problem of enhancement of amateur photos damaged by backlighting for printing. The purpose of correction is to make photos more pleasant for an observer. Photos with exposure problems and with poorly distinguishable details in dark areas are main subject of our research. Our approach is based on contrast stretching and alpha-blending of both brightness of the initial image and estimations of reflectance. For obtaining reflectance estimation a simplified illumination model is used. The luminance is estimated using bilateral filter. Reflectance is estimated using heuristic functions of ratio between brightness of the initial image and estimation of luminance. The correction parameters are chosen adaptively based on histogram analysis. Noise suppression and some sharpening occur during correction. Also the time and memory optimization issues are considered. Recursive separable bilateral filter is applied to speed up the algorithm. The quality of the algorithm is evaluated by surveying of observer’s opinions and by comparisons with already existing software and hardware solutions for local shadow correction.