Example-based learning for single-image super-resolution and JPEG artifact removal

This paper proposes a framework for single-image super-resolution and JPEG artifact removal. The underlying idea is to learn a map from input low-quality images (suitably preprocessed low-resolution or JPEG encoded images) to target high-quality images based on example pairs of input and output images. To retain the complexity of the resulting learning problem at a moderate level, a patch-based approach is taken such that kernel ridge regression (KRR) scans the input image with a small window (patch) and produces a patchvalued output for each output pixel location. These constitute a set of candidate images each of which reflects different local information. An image output is then obtained as a convex combination of candidates for each pixel based on estimated confidences of candidates. To reduce the time complexity of training and testing for KRR, a sparse solution is found by combining the ideas of kernel matching pursuit and gradient descent. As a regularized solution, KRR leads to a better generalization than simply storing the examples as it has been done in existing example-based super-resolution algorithms and results in much less noisy images. However, this may introduce blurring and ringing artifacts around major edges as sharp changes are penalized severely. A prior model of a generic image class which takes into account the discontinuity property of images is adopted to resolve this problem. Comparison with existing super-resolution and JPEG artifact removal methods shows the effectiveness of the proposed method. Furthermore, the proposed method is generic in that it has the potential to be applied to many other image enhancement applications

Wetting Behavior of Dental Implants

Titanium (Ti) and titanium alloys are widely used in biomedical devices and components, because of their desirable properties, such as relatively low modulus, good fatigue strength, formability, machinability, corrosion resistance, and biocompatibility. However, Ti and its alloys cannot meet all of the clinical requirements. Therefore, surface modification of Ti has been often performed to improve the biological, chemical, and mechanical properties. Various modifications of surface properties have been investigated to predictably improve the osseointegration of Ti implants. The rate and quality of osseointegration in Ti implants are related to their surface properties. A multiplicity of implant surface forms exist engineered with mechanical features that physically interlock the implant with bone. Various strategies have been utilized to improve bone integration of Ti-based implants. For example, surface grit blasting, acid-etching and anodization methods enhance cell growth, improving implant fixation through increases in interlocking surface area and alterations of oxide thickness. On the other hand, surface composition and hydrophilicity are parameters that may play a role in implant-tissue interaction and osseointegration. Highly hydrophilic surfaces seem more desirable than hydrophobic ones in view of their interactions with biological fluids, cells and tissues. Several recent studies have shown that the surface energy of biomaterials strongly has influence the initial cell attachment and spreading of osteoblastic cells on the biomaterial surfaces. Hallab et al. said that surface energy might be a more important determinant of cell adhesion and proliferation, and might be more useful than surface roughness for generating cell adhesion and cell. It may have the influence on protein adsorption and the structural rearrangement of the proteins on the material. Therefore, understanding the relationship between surface energy and cell adhesion on different biomaterials will facilitate the design of optimized implant material surfaces and subsequently the cell attachment. Surface energy is an important parameter of the material surface. It is affected by several surface characteristics, such as chemical composition, surface charge, and microstructural topography. Many papers reported that surface energy is one of important surface characteristics parameter of modified titanium surfaces. Given the importance of surface wettability of dental implants surfaces in the achievement of osseointegration, the surface free energy values for a given material, obtained by various methods and with use of different measuring liquids, are not consistent. Thus, we provided a review article of the surface modification on titanium surface and the surface wettability. The relationship between CAs and surface preparations was determined in this review