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基于遗传算法的图像自适应模糊增强 总被引:3,自引:0,他引:3
提出了一种新的基于模糊理论的图像质量的测量函数,把它作为遗传算法的适应度函数对非完全Beta函数的α和β参数进行自适应动态调节来拟合几种典型的灰度变换曲线,实现了灰度图像的自动对比度增强。选择HSI的颜色模式,实现把灰度图像增强算法拓展到彩色图像的增强。无论灰度还是彩色像,实验结果表明:该方法不仅能使图像的对比度得到改善,而且能很好的保存局部信息,具有较高的自适应性;对于灰度图像,其在性能上优于传统的图像增强技术和现有的一些同类增强技术;对于彩色图像,这种方法既得到了清晰的彩色图像,又保护了原有的彩色信息,而且图像像质还强于传统的图像增强技术和Photoshop软件处理的效果。 相似文献
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彩色滤波阵列(CFA)格式的图像需要进行图像插值,才能获得全彩色图像.但是,由于相机噪声的存在,不仅该点的彩色信息失真,同时还会影响邻近像素利用该点信息进行插值的图像颜色.为了得到高质量的全彩色图像,采用了一种基于梯度的滤噪插值算法,在保留了图像边缘和细节信息的同时,滤除了噪声,使图像的信噪比提高了近1倍;由于这种数字相机没有白平衡处理,使插值恢复的彩色图像颜色与实际景物相比存在较大差异,为了消除这种差异,实现了自适应白平衡校正方法,使图像方差提高了近20%,与人眼观察到实际景物的颜色更接近;整个彩色编码算法应用了DSP的并行流水线技术,保证了其在DSP上运行的实时性,处理频率达到25Hz. 相似文献
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针对被广泛应用于战场侦察的彩色图像及红外图像,提出了一种应用离散小波框架的融合处理与彩色空间变换相结合的处理方法实现这2类图像的融合技术。给出了这种融合技术的流程和处理步骤,并用彩色图像和红外图像进行了融合算法测试,计算了融合图像与源图像的条件交互信息量。试验证明采用这种融合处理后的结果图像能够保留彩色图像的高分辨率和真实的色彩信息,同时包含红外图像发现的隐藏的武器目标信息。 相似文献
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低照度彩色图像增强在生活中起着重要作用,传统的低照度彩色图像增强算法往往会引起图像的不同程度失真。为了增强低照度彩色图像而又不引起图像失真,本文提出了一种新的低照度图像自适应对比度增强算法。将分数阶微积分、传统Retinex变分法与分段对数变换饱和度增强法相结合,构造一种新的分数阶Retinex图像增强算法。实验结果表明,该方法具有增强图像对比度的同时又能保持边缘和纹理细节的能力。与传统低照度图像增强算法相比,能突出图像的细节纹理信息,同时图像色度和亮度也有明显改善。 相似文献
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基于颜色色差的彩色图像压缩技术研究 总被引:2,自引:1,他引:1
根据图像DCT变换域系数特征和结合人眼辨别颜色色差的阈值,提出了一种基于颜色色差的彩色图像压缩技术方案。方案首先将彩色图像转化到与设备无关的CIELAB颜色空间,并进行DCT变换和色差计算;再通过人眼辨别颜色色差的阈值进行有选择的量化,并通过Huffman算法进行编码、压缩;最后利用其逆过程进行解压。通过仿真实验,结果表明,重建的彩色解压缩图像与源图像几乎一样,各分量亮度图的解压缩图像的PSNR均超过30dB,人眼几乎不能分辨其差异;衡量编码质量优劣的5个参数值均达到较好效果,且在保证解压缩图像质量的情况下,彩色图像的压缩比能够达到107.167 8,完全可以满足彩色图像压缩的需求。结果表明,提出的基于颜色色差的图像压缩技术方案是一种可行的、较好的彩色图像压缩技术。 相似文献
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针对左聚焦和右聚焦彩色图像的融合问题,设计了一种基于边缘检测的彩色图像融合算法。首先将彩色图像转换为NTSC图像,再利用Canny方法检测出亮度信息图像的最优边缘,然后对亮度信息图像的边缘部分采用平均法进行融合,其余部分采用相关系数的权值法进行融合,最后将融合之后的饱和度图像、亮度图像和色调图像转换为彩色图像。从融合效果来看,文中算法能够将两幅左右聚焦的彩色图像融合成一幅信息量饱满且清晰的单一聚焦彩色图像。实验结果和信息熵客观评价结论表明,该彩色融合算法能够将信息熵提高2.13%~2.51%。 相似文献
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The visual efficiency of an image compression technique depends directly on the amount of visually significant information it retains. By "visually significant" we mean information to which a human observer is most sensitive. The overall sensitivity depends on aspects such as contrast, color, spatial frequency, and so forth. One important aspect is the inverse relationship between contrast sensitivity and spatial frequency. This is described by the contrast sensitivity function (CSF). In compression algorithms the CSF can be exploited to regulate the quantization step-size to minimize the visibility of compression artifacts. Existing CSF implementations for wavelet-based image compression use the same quantization step-size for a large range of spatial frequencies. This is a coarse approximation of the CSF. This paper presents two new techniques that implement the CSF at significantly higher precision, adapting even to local variations of the spatial frequencies within a decomposition subband. The approaches can be used for luminance as well as color images. For color perception three different CSFs describe the sensitivity. The implementation technique is the same for each color band. Implemented into the JPEG2000 compression standard, the new techniques are compared to conventional CSF-schemes. The proposed techniques turn out to be visually more efficient than previously published methods. However, the emphasis of this paper is on how the CSF can be implemented in a precise and locally adaptive way, and not on the superior performance of these techniques. 相似文献
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本文研究了利用多极化合成孔径雷达(SAR)数据产生极化伪彩色合成图的方法,提出了用M11归一化后得到的Stokes矩阵来产生目标的极化合成孔径雷达伪彩色图的新方法.由于它消除了目标总功率大小对图像色彩的影响,因而可以分析场景回波功率太强或太弱目标与极化特征图具有相同形状的目标.另外,还提出用极化特征图方法求出三种极化组合,使两类目标的回波功率相差达到最大,再合成处理成极化合成孔径雷达伪彩色合成图的方法. 相似文献
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Philippe Carré Patrice Denis Christine Fernandez-Maloigne 《Signal, Image and Video Processing》2014,8(7):1357-1372
In the literature, the color information of the pixels of an image has been represented by different structures. Recently, algebraic entities such as quaternions or Clifford algebras have been used to perform image processing for example. This paper presents the embedding of color information into the vectorial parts of a multivector. This multivector is an element of the geometric or Clifford algebra constructed from a three-dimensional vector space. This formalism presents the advantage of algebraically separating colors which are handled entities from the geometric operations done to them. We propose to introduce several contributions for color image processing by using this Clifford algebra. First, as colors are represented by 1-vectors, we point out that a color pixel given in the RGB color space can be expressed algebraically by its hue saturation and value using the geometry. Then, we illustrate how this formalism can be used to define color alterations with algebraic operations. We generalize linear filtering algorithms already defined with quaternions and define a new color edge detector. Finally, the application of the new color gradient is illustrated by a new color formulation of snakes. Thus, we propose in this paper the definition and exploitation of a formalism in which we geometrically handle colors with algebraic entities and expressions. 相似文献
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基于德劳内三角剖分的彩色图像加权直方图表示及检索技术 总被引:2,自引:1,他引:1
经典的颜色直方图方法存在诸多缺陷,例如它不能表示图像中颜色的空间分布信息。为了进一步的提高图像检索能力,在分析图像特征的基础上,文章给出了一种基于角度图的直方图加权的图像表示方法。这种方法不仅保持了图像直方图简单方便的特点,同时又有效地将颜色的空间分布信息集成到直方图中。实验结果表明,对比经典直方图表示这种彩色图像的表示方法能获得更好的检索效果。 相似文献
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In Content Based Image Retrieval (CBIR) system, the exhaustive search for a given query image to find the relevant images in the database are non-scalable. In this paper, we propose indexing, coding technique and similarity measure to address the above mentioned problem. We consider the color histogram of the image and its bin values are analyzed to understand the color information in the image. The histogram dimension is reduced by removing trivial bins and only those bins that represent color information significantly are considered. Based on the dimensions of the histogram, it is clustered and indexed. The Golomb–Rice (GR) coding is used to encode the indexed histograms. The Bin Overlapped Similarity Measure (BOSM) is proposed to compute the distance values between query and database image histograms. The performance of proposed approach is evaluated on benchmark datasets and found that the performance of the proposed approach is encouraging. 相似文献
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Multispectral image visualization through first-order fusion 总被引:8,自引:0,他引:8
We present a new formalism for the treatment and understanding of multispectral images and multisensor imagery based on first-order contrast information. Although little attention has been paid to the utility of multispectral contrast, we develop a theory for multispectral contrast that enables us to produce an optimal grayscale visualization of the first-order contrast of an image with an arbitrary number of bands. We demonstrate how our technique can reveal significantly more interpretive information to an image analyst, who can use it in a number of image understanding algorithms. Existing grayscale visualization strategies are reviewed. A variety of experimental results are presented to support the performance of the new method. 相似文献