Medical image enhancement algorithm based on NSCT and the improved fuzzy contrast

In order to solve the problem of noise amplification, low contrast and image distortion in the process of medical image enhancement, a new algorithm is proposed which combines NSCT (nonsubsampled contourlet transform) and improved fuzzy contrast. The image is decomposed by NSCT. Firstly, linear enhancement method is used in low frequency coefficients; secondly the improved adaptive threshold function is used to deal with the high frequency coefficients. Finally, the improved fuzzy contrast is used to enhance the global contrast and the Laplace operator is used to enhance the details of the medical images. Experimental results show that the proposed algorithm can improve the image visual effects, remove the noise and enhance the details of medical images. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 7–14, 2015     

多颜色空间的内窥镜图像血管增强方法

为了提高医用电子内窥镜所获图像的血管与组织的对比度,针对内窥镜血管图像的特点,提出了一种基于多颜色空间非线性对比度拉伸的血管增强处理方法。首先在RGB颜色空间利用非线性映射函数对绿色(G)分量进行自适应对比度拉伸;接着依据G分量的拉伸结果,相应地调整红色(R)和蓝色(B)两个分量的灰度值;然后将图像转换到HSV颜色空间,并对图像的饱和度(S)分量进行自适应对比度拉伸;最后将图像转换回RGB颜色空间,最终达到血管增强的目的。在本文中,利用所提出的算法对多幅电子内窥镜图像进行处理,结果表明,算法对于原始特征不明显的细小血管也具有较好的增强效果。通过与其它的增强方法相对比,增强后图像的细节方差(DV)显著大于其它方法。将算法嵌入到分辨率为1280×800的内窥镜软件中,其处理速度可达26 f/s。     

Brightness preserving bi‐level fuzzy histogram equalization for MRI brain image contrast enhancement

In this article, brightness preserving bi‐level fuzzy histogram equalization (BPFHE) is proposed for the contrast enhancement of MRI brain images. Histogram equalization (HE) is widely used for improving the contrast in digital images. As a result, such image creates side‐effects such as washed‐out appearance and false contouring due to the significant change in brightness. In order to overcome these problems, mean brightness preserving HE based techniques have been proposed. Generally, these methods partition the histogram of the original image into sub histograms and then independently equalize each sub‐histogram. The BPFHE consists of two stages. First, fuzzy histogram is computed based on fuzzy set theory to handle the inexactness of gray level values in a better way compared to classical crisp histograms. In the second stage, the fuzzy histogram is divided into two sub‐histograms based on the mean intensities of the multi‐peaks in the original image and then equalizes them independently to preserve image brightness. The quantitative and subjective enhancement of proposed BPBFHE algorithm is evaluated using two well known parameters like entropy or average information contents (AIC) and Feature Similarity Index Matrix (FSIM) for different gray scale images. The proposed method have been tested using several images and gives better visual quality as compared to the conventional methods. The simulation results show that the proposed method has better performance than the existing methods, and preserve the original brightness quite well, so that it is possible to be utilized in medical image diagnosis.     

MRI brain image enhancement using brightness preserving adaptive fuzzy histogram equalization

In this article, fuzzy logic based adaptive histogram equalization (AHE) is proposed to enhance the contrast of MRI brain image. Medical image plays an important role in monitoring patient's health condition and giving an effective diagnostic. Mostly, medical images suffer from different problems such as poor contrast and noise. So it is necessary to enhance the contrast and to remove the noise in order to improve the quality of a various medical images such as CT, X‐ray, MRI, and MAMOGRAM images. Fuzzy logic is a useful tool for handling the ambiguity or uncertainty. Brightness Preserving Adaptive Fuzzy Histogram Equalization technique is proposed to improve the contrast of MRI brain images by preserving brightness. Proposed method comprises of two stages. First, fuzzy logic is applied to an input image and then it's output is given to AHE technique. This process not only preserves the mean brightness and but also improves the contrast of an image. A huge number of highly MRI brain images are taken in the proposed method. Performance of the proposed method is compared with existing methods using the parameters namely entropy, feature similarity index, and contrast improvement index and the experimental results show that the proposed method overwhelms the previous existing methods.     

Image contrast enhancement with brightness preservation using an optimal gamma correction and weighted sum approach

The enhancement of image contrast and preservation of image brightness are two important but conflicting objectives in image restoration. Previous attempts based on linear histogram equalization had achieved contrast enhancement, but exact preservation of brightness was not accomplished. A new perspective is taken here to provide balanced performance of contrast enhancement and brightness preservation simultaneously by casting the quest of such solution to an optimization problem. Specifically, the non-linear gamma correction method is adopted to enhance the contrast, while a weighted sum approach is employed for brightness preservation. In addition, the efficient golden search algorithm is exploited to determine the required optimal parameters to produce the enhanced images. Experiments are conducted on natural colour images captured under various indoor, outdoor and illumination conditions. Results have shown that the proposed method outperforms currently available methods in contrast to enhancement and brightness preservation.     

一种高通量dPCR荧光图像自适应增强算法

目的 为了改善荧光图像背景光照不均匀和对比度低的问题,提出一种荧光图像自适应亮度校正和低对比度增强算法。方法 根据光照成像原理,利用引导滤波提取出荧光图像的光照分量,通过改进的二维Gamma函数动态校正背景光照,利用Top-hat变换分离出校正后的前景和背景,对前景进行自适应直方图均衡化,以实现荧光图像自适应增强的目的。结果 对比传统算法,文中算法处理后的图像背景光照均匀,对比度增强效果明显,其中标准差平均提高了9.4倍,平均梯度平均提高了1.2倍,信息熵平均提高了0.2倍。结论 文中算法可以改善高通量dPCR荧光图像背景光照不均匀性,提高图像对比度,突出图像中隐藏的细节,对其他荧光图像处理也具有参考价值。     

A bioinspired path planning approach for mobile robots based on improved sparrow search algorithm

In this paper, a bioinspired path planning approach for mobile robots is proposed. The approach is based on the sparrow search algorithm, which is an intelligent optimization algorithm inspired by the group wisdom, foraging, and anti-predation behaviors of sparrows. To obtain high-quality paths and fast convergence, an improved sparrow search algorithm is proposed with three new strategies. First, a linear path strategy is proposed, which can transform the polyline in the corner of the path into a smooth line, to enable the robot to reach the goal faster. Then, a new neighborhood search strategy is used to improve the fitness value of the global optimal individual, and a new position update function is used to speed up the convergence. Finally, a new multi-index comprehensive evaluation method is designed to evaluate these algorithms. Experimental results show that the proposed algorithm has a shorter path and faster convergence than other state-of-the-art studies.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00366-x     

An Optimum Shift-and-Weighted brightness mapping for low-illumination image restoration

Images captured under low-illumination environments often impose difficulties in revealing objects of interest. An effective approach, Optimum Shift-and-Weighted Brightness Mapping, is here proposed that can optimally enhance the image for higher brightness, information content, and colour vividness. Specifically, the input-output brightness mapping is determined by a shifted spline curve and a larger amplification is allowed for low-brightness pixels. A weighting function is further applied such that high brightness pixels are preserved. The final enhanced image is obtained by inserting the extracted high frequency components from the original input to the brightness boosted image. The algorithm is adaptive to image contents where parameters are optimized using the efficient golden section search instead of relying on user specified coefficients. Experimental results, from a large set of test images, showed that better quality images could be obtained on a variety of low-illumination scenarios as compared to several recent approaches.     

A Post-Processing Algorithm for Boosting Contrast of MRI Images

Low contrast of Magnetic Resonance (MR) images limits the visibility of subtle structures and adversely affects the outcome of both subjective and automated diagnosis. State-of-the-art contrast boosting techniques intolerably alter inherent features of MR images. Drastic changes in brightness features, induced by post-processing are not appreciated in medical imaging as the grey level values have certain diagnostic meanings. To overcome these issues this paper proposes an algorithm that enhance the contrast of MR images while preserving the underlying features as well. This method termed as Power-law and Logarithmic Modification-based Histogram Equalization (PLMHE) partitions the histogram of the image into two sub histograms after a power-law transformation and a log compression. After a modification intended for improving the dispersion of the sub-histograms and subsequent normalization, cumulative histograms are computed. Enhanced grey level values are computed from the resultant cumulative histograms. The performance of the PLMHE algorithm is compared with traditional histogram equalization based algorithms and it has been observed from the results that PLMHE can boost the image contrast without causing dynamic range compression, a significant change in mean brightness, and contrast-overshoot.     

一种基于YC-rC-b颜色空间和视觉特性的彩色图像水印技术

根据图像离散余弦变换频谱图特征及结合人眼对亮度和颜色的对比度敏感视觉特性,提出了一种人眼感知图像最小误差即JND阈值的计算方法,通过计算出的JND阈值,提出了一种基于YCrCb颜色空间的彩色图像水印技术方案。方案依据JND阈值筛选彩色图像的3个分量亮度图变换域频谱系数来进行水印的嵌入和提取。从水印技术方案上看,JND阈值的引入使得水印的嵌入达到最大;嵌入算法使得水印嵌入的位置具有随机性,有力地保证了水印信息的安全性。仿真实验和攻击测试表明:含水印图经压缩攻击后的图像与原始图像基本一样,提取的水印信息与原始水印基本相同;攻击后的含水印图具有较好的透明性和较高的鲁棒性。提出的基于YCrCb颜色空间和人眼视觉特性的彩色图像水印技术方案,是一种可行的、较好的彩色图像技术。     

改进麻雀算法求解带模糊需求的低碳路径优化

目的 针对低碳背景下带模糊需求的低碳多式联运规划问题（Low-carbon Multimodal Transportation Planning Problem with Fuzzy Demand, LCMTPP-FD），以成本最小化构建数学模型。同时，结合现有的强制碳排放、碳税、碳交易和碳补偿等政策对LCMTPP-FD进行模型转换，研究不同低碳政策对物流成本和碳排放量的影响。方法 主要根据模型的特征，设计一种t分布麻雀搜索算法，对不同低碳政策下的模型进行求解，将迭代次数作为t分布的自由度来提高麻雀算法的性能。结果 将改进算法及多个模型应用于实际运输案例中，改进的麻雀算法能在较短时间内获得最优解，并且在强制碳排放下碳排放量最少为9 522.28，在碳交易和碳补偿政策下成本分别降低了11.41%、17.24%。结论 改进的麻雀搜索算法具有较好的收敛性和搜索能力。强制碳排放能有效地降低碳排放量，碳交易和碳补偿能有效降低企业成本，适合于低碳运输的推广。     

An efficient and high quality medical CT image enhancement algorithm

Aiming at the process of medical diagnosis, many problems such as unclear images and low contrast are often caused by noise and interference in the process of medical image acquisition and transmission. This article proposes a new image enhancement method that combines the wavelet domain with the spatial domain. First, we input two identical images (Both of the identical images are original images.) in which the first image is enhanced by histogram equalization. Then, the two images are divided into four sub-images by a two-dimensional wavelet transform. The average of the low-frequency coefficients of the low-frequency sub-images of the two images is taken as the low-frequency coefficients of the final reconstruction. Second, aiming at the problem that the contrast may be too low, the fourth high-frequency sub-image is blurred (sharpened) twice. The fourth high-frequency sub-image after blurring is denoised by median filtering. Finally, the four sub-images are fused to obtain the enhanced image. The experimental results show that the peak signal-to-noise ratio, structural similarity, and processing time of the proposed algorithm are better than those of other contrast algorithms, especially the processing time. These objective indicators show that the proposed algorithm can not only effectively suppress noise but also significantly enhance the contrast. Subjectively, compared with other algorithms, the proposed algorithm achieves a better visual effect and greatly reduces the processing time.     

Two level security for medical images using watermarking/encryption algorithms

In this article, an attempt is made to provide two level securities for medical images using watermarking and encryption. Watermarking provides security and encryption, authenticates medical image and provides integrity. Watermarking is performed by using a new nontensor product wavelet filter banks, which have the ability to reveal singularities in different directions. Natural image is taken as the original image and the medical image is taken as a watermark image. The medical image is embedded into the LH sub band of the natural image. The encryption is performed by RSA, AES, and RC4 algorithms. A qualitative comparative analysis of the proposed algorithm is done for different encryption methods. The proposed algorithm has the ability to withstand different attacks like noise, rotation, contrast, and brightness attacks. Performance analysis is made by calculating PSNR, SSIM, NC, and CV.     

改进麻雀搜索算法求解多目标低碳冷链物流车辆路径问题

目的 在传统冷链物流的车辆路径问题模型基础上,考虑服务节点和车辆运输过程中产生的碳排放,并加入客户满意度,在有限资源情况下最小化路径成本和最大化客户满意度。方法 构建多目标低碳冷链物流车辆路径问题模型,将爬山算法局部搜索思想应用到麻雀搜索算法中,形成改进麻雀搜索算法,并用其对上海市某区域内的冷链物流配送路径优化问题算例进行求解。结果 通过与改进前及其他2种智能优化算法运行结果进行对比发现,改进后的麻雀搜索算法具有更快的寻优速度和更好的寻优能力,且改进后的算法对模型的碳排放效用性更高。结论 基于国家的低碳政策,设计出符合当下实情的低碳冷链物流运输模型,通过改进优化算法设计运输方案,验证了爬山算法局部搜索思想对麻雀搜索算法进行改进的有效性及所构建低碳冷链物流车辆路径模型的合理性。     

一种基于颜色恒常性的低照度图像增强方法

目的在彩色图像采集过程中,光源偏暗或曝光不足等因素常导致图像亮度和对比度偏低。提出一种基于颜色恒常性的低照度图像增强方法。方法利用HSV颜色空间消除颜色分量之间的相关性。保持色调分量不变,避免颜色失真;一方面使用改进后的MSR(多尺度Retinex)算法对亮度分量进行增强,提高图像的亮度和对比度;另一方面对饱和度分量进行自适应非线性拉伸以提高颜色的饱和度。结果提出的方法能够有效提高图像的对比度和信息熵,获得较好的视觉效果;将文中方法同传统MSR算法和MSRCR算法进行对比,文中方法各项客观评价指标均优于其他2种算法,并且具有更快的运行速度。结论文中方法能够快速有效地提高低照度图像的亮度和对比度,并且具有较强的颜色保真和细节再现能力,实验结果证明了文中方法的有效性。     

基于NSST多尺度自适应的Retinex低照度图像增强算法

目的在对低照度图像进行增强时,针对传统频率域方法由于尺度不够丰富而不能很好保留图像高频细节的问题,提出一种基于NSST多尺度自适应的Retinex低照度图像增强算法。方法首先将低照度图像转化至HSI颜色空间后,单独对I通道进行处理,实现对图像色彩信息的保真效果;然后对I通道进行Retinex算法得到反射分量,从而去除照度信息对图像亮度的影响;对反射分量进行伽马调整后,进行基于La(平均亮度)、Pa(平均对比度)、Ia(信息熵)等3个特征值的自适应NSST分解,从而得到最佳参数的高频分量。结果在主观观察和客观无参考图像质量评价中,文中算法的增强效果和评价得分都要优于其他算法。结论经过自适应参数优化之后,低照度图像的对比度得到了提高,可视性和图像质量都得到了显著提升。     

Palmprint enhancement using recursive histogram equalisation

Abstract

Palmprint identification system is one of the most powerful personal identification systems in recent years. In order to achieve high identification accuracy, all parts of the palmprint are needed to be enhanced. Histogram equalisation is a very popular image enhancing technique. A novel histogram equalisation technique, called recursive\ histogram equalisation, for brightness preservation and image contrast enhancement, is put forward in this paper. The essence of proposed algorithm is to decompose an input histogram into two or more sub-histograms recursively based on its mean, change the sub-histograms through a weighting process based on a normalised power law function and then equalise the weighted sub-histograms independently. Experiments show that our method preserves the mean brightness of a given image, enhances the contrast and produces more natural looking images than the other histogram equalisation methods.     

Correlation of image quality with exposure index and processing protocol in a computed radiography system

The correlation of image quality with the exposure index (EI)and the processing protocol was investigated in a Kodak computedradiography (CR) system using clinical radiographs and a waterphantom containing an aluminium and a copper stepwedge. Thephantom was exposed to different dose levels and the acquiredimages were processed using four clinical protocols. The qualityof these images was evaluated in terms of image brightness,contrast and noise. In clinical radiographs, there was no straightforwardcorrelation of image quality with EI. In phantom images, higherEI values improved contrast and reduced noise but after a pointthis improvement does not justify the implied increase in patientdose. Image brightness, contrast and noise were also stronglydependent on the processing protocol. To obtain the images ofsatisfactory quality with the Kodak CR system, a dose slightlyhigher than those used in 400 relative speed screen–filmsystems and a processing protocol designated for the specificradiographic examination are required.     

Hybrid Ultrasonic TOFD Imaging of Weld Flaws Using Wavelet Transforms and Image Registration

Ultrasonic time of flight diffraction (TOFD) is an effective weld crack inspection technique. Due to the intensity of diffraction wave is rather weak compared with the lateral wave and the bottom echo wave, thus the signal-to-ratio (SNR) of TOFD image is low. A new dichotomous method is comprised of two steps that contains wavelet shrinkage and image registration is proposed in this paper to reduce the noise and improve the resolution of TOFD images as well. In order to evaluate the reliability of our proposed method in this paper, we have established the experiment system, and sampled a number of TOFD data with random distribution of noise characteristics. We adopted one-dimension wavelet transform and two-dimension wavelet transform in the very beginning of the first step of the proposed algorithm respectively. The SNR of the result obtained in this step is improved significantly compared with the classic algorithms. Next, the image registration is applied. After the registered images have been added to form a new one, then it comes to the final result that shows not only the SNR but also the definition of the image is enhanced effectively.     

Gaussian probability bi-histogram equalization for enhancement of the pathological features in medical images

In order to enhance the pathological features of medical images and aid the medical diagnosis, the image enhancement is a necessary process. This study presented the Gaussian probability model combining with bi-histogram equalization to enhance the contrast of pathological features in medical images. There are five different bi-histogram equalizations, namely, bi-histogram equalization (BBHE), dualistic sub-image histogram equalization (DSIHE), bi-histogram equalization with a plateau limit (BHEPL), bi-histogram equalization median plateau limit (BHEPL-D), and bi-histogram equalization with modified histogram bins (BHEMHB). The entropy, contrast, absolute mean brightness error (AMBE), and skewness difference are used to quantize the enhancement results. From the experimental result, it is observed that the entropy and contrast of the images can be effectively enhanced by using Gaussian probability bi-histogram equalizations, and the Gaussian probability bi-histogram equalization median plateau limit (GPBHEPL-D) has the best enhanced result. The proposed GPBHEPL-D method is effective in strengthening the pathological features in medical images, so as to increase the efficiency of doctors' diagnoses and computer-aided detection.