为给低剂量CT(computed tomography)图像提供准确的客观评价指标,对常用的图像客观评价指标进行验证和比较分析。选用LIVE(laboratory for image and video engineering)综合图库对各个图像指标的性能进行验证分析,对不同剂量的体模CT...为给低剂量CT(computed tomography)图像提供准确的客观评价指标,对常用的图像客观评价指标进行验证和比较分析。选用LIVE(laboratory for image and video engineering)综合图库对各个图像指标的性能进行验证分析,对不同剂量的体模CT图像进行客观评价。实验结果表明,基于马尔科夫随机场的互信息比其它指标更明显、准确地反映综合图库与低剂量CT图像的质量变化,能够为低剂量CT图像质量评价提供有力参考。展开更多
The texture analysis is often discussed in image processing domain, but most methods are limited within gray-level image or color image, and the present conception of texture is defined mainly based on gray-level imag...The texture analysis is often discussed in image processing domain, but most methods are limited within gray-level image or color image, and the present conception of texture is defined mainly based on gray-level image of single band. One of the essential characters of remote sensing image is multidimensional or even high-dimensional, and the traditional texture conception cannot contain enough information for these. Therefore, it is necessary to pursuit a proper texture definition based on remote sensing images, which is the first discussion in this paper. This paper describes the mapping model of spectral vector in two-dimensional image space using Markov random field (MRF), establishes a texture model of multiband remote sensing image based on MRF, and analyzes the calculations of Gibbs potential energy and Gibbs parameters. Further, this paper also analyzes the limitations of the traditional Gibbs model, prefers a new Gibbs model avoiding estimation of parameters, and presents a new texture segmentation algorithm for hy-perspectral remote sensing image later.展开更多
文摘为给低剂量CT(computed tomography)图像提供准确的客观评价指标,对常用的图像客观评价指标进行验证和比较分析。选用LIVE(laboratory for image and video engineering)综合图库对各个图像指标的性能进行验证分析,对不同剂量的体模CT图像进行客观评价。实验结果表明,基于马尔科夫随机场的互信息比其它指标更明显、准确地反映综合图库与低剂量CT图像的质量变化,能够为低剂量CT图像质量评价提供有力参考。
基金Supported by the National Key Basic Research and Development Program(No.2006CB701303, No. 2004CB318206)
文摘The texture analysis is often discussed in image processing domain, but most methods are limited within gray-level image or color image, and the present conception of texture is defined mainly based on gray-level image of single band. One of the essential characters of remote sensing image is multidimensional or even high-dimensional, and the traditional texture conception cannot contain enough information for these. Therefore, it is necessary to pursuit a proper texture definition based on remote sensing images, which is the first discussion in this paper. This paper describes the mapping model of spectral vector in two-dimensional image space using Markov random field (MRF), establishes a texture model of multiband remote sensing image based on MRF, and analyzes the calculations of Gibbs potential energy and Gibbs parameters. Further, this paper also analyzes the limitations of the traditional Gibbs model, prefers a new Gibbs model avoiding estimation of parameters, and presents a new texture segmentation algorithm for hy-perspectral remote sensing image later.
