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Color quantization is a common image processing technique where full color images are to be displayed using a limited palette of colors. The choice of a good palette is crucial as it directly determines the quality of the resulting image. Standard quantization approaches aim to minimize the mean squared error (MSE) between the original and the quantized image, which does not correspond well to how humans perceive the image differences. In this article, we introduce a color quantization algorithm that hybridizes an optimization scheme based with an image quality metric that mimics the human visual system. Rather than minimizing the MSE, its objective is to maximize the image fidelity as evaluated by S‐CIELAB, an image quality metric that has been shown to work well for various image processing tasks. In particular, we employ a variant of simulated annealing with the objective function describing the S‐CIELAB image quality of the quantized image compared with its original. Experimental results based on a set of standard images demonstrate the superiority of our approach in terms of achieved image quality. 相似文献
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针对胃上皮肿瘤细胞图像(以下简称肿瘤细胞图像)黏结严重和信息冗余的特点,提出了一种将自适应观测矩阵的压缩感知(SAM-CS)和自组织特征映射(SOFM)神经网络相结合的算法。该算法将肿瘤细胞图像拉成列向量,然后利用通过自适应过程产生的观测矩阵,基于压缩感知理论对图像信息进行观测,产生线性观测向量,最后利用SOFM神经网络的学习算法对观测向量进行训练和分类,实现对肿瘤细胞图像的识别。实验表明,相比常用算法,该算法至少提高了4.2%的识别准确率和5.7%的运算速度。 相似文献
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为解决折反射全景成像系统中的采样分辨率与帧速之间的矛盾,通过反馈控制图像传感器的参数配置,设计并实现了一个全局与局部双模式的全景成像处理系统.在全局模式下,为保证采集帧速率,使用行列跳跃模式采集完整的环状全向图,并将其展开为包含360°全局信息的柱面全景图像;在局部模式下,根据感兴趣区域的空间位置设置采样窗口大小及位置,以逐像素采样模式只采集全向图中相应的一块矩形区域,并将其展开为对应视线方向上高清晰度的局部透视图;最后给出了DSP+FPGA结构的系统硬件设计方案.实验结果表明了该系统设计的科学性及实用性. 相似文献
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合成孔径雷达(SAR)图像产生的相干斑噪声是一种乘性噪声,严重影响SAR图像的质量.本文提出一种新的极化SAR图像的去噪方法,该方法对极化SAR图像进行自适应Bandelets阈值方法,阈值采用BayesShrink软阈值方法,将其应用于自适应Bandelets系数.通过实验对比,证实此法与小波阈值去噪相比,能够更好地... 相似文献
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Marcelo Siqueira Longin Jan Latecki Nicholas Tustison Jean Gallier James Gee 《Journal of Mathematical Imaging and Vision》2008,30(3):249-274
We present here a new randomized algorithm for repairing the topology of objects represented by 3D binary digital images.
By “repairing the topology”, we mean a systematic way of modifying a given binary image in order to produce a similar binary
image which is guaranteed to be well-composed. A 3D binary digital image is said to be well-composed if, and only if, the square faces shared by background and foreground
voxels form a 2D manifold. Well-composed images enjoy some special properties which can make such images very desirable in
practical applications. For instance, well-known algorithms for extracting surfaces from and thinning binary images can be
simplified and optimized for speed if the input image is assumed to be well-composed. Furthermore, some algorithms for computing
surface curvature and extracting adaptive triangulated surfaces, directly from the binary data, can only be applied to well-composed
images. Finally, we introduce an extension of the aforementioned algorithm to repairing 3D digital multivalued images. Such
an algorithm finds application in repairing segmented images resulting from multi-object segmentations of other 3D digital
multivalued images.
相似文献
James GeeEmail: |
30.
A. Z. Kouzani 《Machine Vision and Applications》2008,19(4):223-248
There has been an increasing interest in face recognition in recent years. Many recognition methods have been developed so
far, some very encouraging. A key remaining issue is the existence of variations in the input face image. Today, methods exist
that can handle specific image variations. But we are yet to see methods that can be used more effectively in unconstrained
situations. This paper presents a method that can handle partial translation, rotation, or scale variations in the input face
image. The principal is to automatically identify objects within images using their partial self-similarities. The paper presents
two recognition methods which can be used to recognise objects within images. A face recognition system is then presented
that is insensitive to limited translation, rotation, or scale variations in the input face image. The performance of the
system is evaluated through four experiments. The results show that the system achieves higher recognition rates than those
of a number of existing approaches.
The author would like to thank the Australian Research Council (ARC) which supports this research with a Discovery Grant. 相似文献