The logarithmic model is often used to describe the relationships between factors.It often gives good statistical characteristics.Yet,in the process of modeling of soil and water conservation,we find out that this“g...The logarithmic model is often used to describe the relationships between factors.It often gives good statistical characteristics.Yet,in the process of modeling of soil and water conservation,we find out that this“good”model cannot guarantee good result.In this paper we make an inquiry into the intrinsic reasons.It is shown that the logarithmic model has the property of enlarging or reducing model errors,and the disadvantages of the logarithmic model are analyzed.展开更多
To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing(LIP) model, this paper proposes what we believe to be an effective image enhancement al...To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing(LIP) model, this paper proposes what we believe to be an effective image enhancement algorithm. This algorithm introduces fuzzy entropy, makes full use of neighborhood information, fuzzy information and human visual characteristics.To enhance an image, this paper first carries out the reasonable fuzzy-3 partition of its histogram into the dark region, intermediate region and bright region. It then extracts the statistical characteristics of the three regions and adaptively selects the parameter αaccording to the statistical characteristics of the image’s gray-scale values. It also adds a useful nonlinear transform, thus increasing the ubiquity of the algorithm. Finally, the causes for the gray-scale value overcorrection that occurs in the traditional image enhancement algorithms are analyzed and their solutions are proposed.The simulation results show that our image enhancement algorithm can effectively suppress the noise of an image, enhance its contrast and visual effect, sharpen its edge and adjust its dynamic range.展开更多
基金Supported by the Ministry of Educational,China(2003-58)the Research Fund for thr Doctoral Programs of the Ministry of Education,China(2002-173)
文摘The logarithmic model is often used to describe the relationships between factors.It often gives good statistical characteristics.Yet,in the process of modeling of soil and water conservation,we find out that this“good”model cannot guarantee good result.In this paper we make an inquiry into the intrinsic reasons.It is shown that the logarithmic model has the property of enlarging or reducing model errors,and the disadvantages of the logarithmic model are analyzed.
基金supported by the National Natural Science Foundation of China(61472324)
文摘To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing(LIP) model, this paper proposes what we believe to be an effective image enhancement algorithm. This algorithm introduces fuzzy entropy, makes full use of neighborhood information, fuzzy information and human visual characteristics.To enhance an image, this paper first carries out the reasonable fuzzy-3 partition of its histogram into the dark region, intermediate region and bright region. It then extracts the statistical characteristics of the three regions and adaptively selects the parameter αaccording to the statistical characteristics of the image’s gray-scale values. It also adds a useful nonlinear transform, thus increasing the ubiquity of the algorithm. Finally, the causes for the gray-scale value overcorrection that occurs in the traditional image enhancement algorithms are analyzed and their solutions are proposed.The simulation results show that our image enhancement algorithm can effectively suppress the noise of an image, enhance its contrast and visual effect, sharpen its edge and adjust its dynamic range.
