An improved detail enhancement algorithm based on difference curvature and contrast field

The gradient image is always sensitive to noise in image detail enhancement. To overcome this shortage, an improved detail enhancement algorithm based on difference curvature and contrast field is proposed. Firstly, the difference curvature is utilized to determine the amplification coefficient instead of the gradient. This new amplification function of the difference curvature takes more neighboring points into account, it is therefore not sensitive to noise. Secondly, the contrast field is nonlinearly amplified according to the new amplification coefficient. And then, with the enhanced contrast field, we construct the energy functional. Finally, the enhanced image is reconstructed by the variational method. Experimental results of standard testing image and industrial X-ray image show that the proposed algorithm can perform well on increasing contrast and sharpening edges of images while suppressing noise at the same time.

Localization and Degree of Damage Based on Relative Curvature Difference and Frequency Perturbation

This study proposed a damage identification method compared with the existing ones,based on relative curvature difference and frequency perturbation theory,showing sensitivity to local damage by changes in the curvature mode and high recognition accuracy of frequencies.Considering the relative curvature difference as a damage index,numerical simulation is used for a simply supported beam under single and multiple damage conditions for different damage degrees.The damage is located according to the curvature mode curves,and the damage degree is qualitatively determined.Based on the perturbation theory,the damage equations are established by the changes between frequencies before and after damage,and the damage localization and degree are verified and determined.Effectiveness of the proposed method for identifying damage at different conditions is numerically investigated.This method potentially promotes the development of damage identification of beam structures.

Fractional-order difference curvature-driven fractional anisotropic diffusion equation for image super-resolution

Image super-resolution methods-based existing edge indicating operators—namely Gauss curvature,mean curvature and gradient-cannot effectively identify the edges,ramps and flat regions and suffer from the loss of fine textures.To address these issues,this paper presents a fractional anisotropic diffusion equation based on a new edge indicator,named fractional-order difference curvature,which can characterize the intensity variations in images.We introduce the frequency-domain definition for fractional-order derivative by the Fourier transform,which is easy to implement numerically.The new edge indicator is better than the existing edge indicating operators in distinguishing between ramps and edges and can better handle the fine textures.Comparative results for natural images validate that the proposed method can yield a visually pleasing result and better values of MSSIM and PSNR.

Three-Step Damage Identification Method Based on Dynamic Characteristics

A three-step damage identification method based on dynamic characteristics is proposed to improve the structure reliability and security and avoid serious accident. In the proposed method, the frequency and difference of modal curvature(DMC) are used as damage indexes. Firstly, the detection of the occurrence of damage is addressed by the frequency or the square of frequency change. Then the damage location inside the structure is measured by the DMC. Finally, with the stiffness reduction rate as a damage factor, the amount of damage is estimated by the optimization algorithm. The three-step damage identification method has been validated by conducting the simulation on a cantilever beam and the shaking table test on a submerged bridge. The results show that the method proposed in this paper can effectively solve the damage identification problem in theory and engineering practice.