High Optical Magnification Three-Dimensional Integral Imaging of Biological Micro-organism

A high optical magnification three-dimensional imaging system is proposed using an optic microscope whose ocular （eyepiece） is retained and the structure of the transmission mode is not destroyed. The elemental image array is captured through the micro lens array. Due to the front diffuse transmission element, each micro lens sees a slightly different spatial perspective of the scene, and a different independent image is formed in each micro lens channel. Each micro lens channel is imaged by a Fourier lens and captured by a CCD. The design translating the stage in x or y provides no parallax. Compared with the conventional integral imaging of micro-objects, the optical magnification of micro-objects in the proposed system can enhanced remarkably. The principle of the enhancement of the image depth is explained in detail and the experimental results are presented.

AN IMAGE MAGNIFICATION ALGORITHM USING THE GVF CONSTRAINT MODEL

An image magnification method with a Gradient Vector Flow(GVF)constraint-basedanisotropic diffusion model is proposed in this letter.A Low-Resolution(LR)image is first magnifiedusing bilinear interpolation,and then an iterative image restoration method,with the use of an ani-sotropic diffusion model and a Gaussian moving-average constraint,is applied to the magnified image.The estimated GVF of a High-Resolution(HR)image can be used to remove the jagged effect and topreserve the textural structure in the image.Meanwhile,the use of the Gaussian moving-average LRmodel can provide a data fidelity constraint,which renders a magnified image closer to the ideal HRversion.Experimental results show that the proposed method can improve the quality of magnifiedimages in terms of both objective and subjective criteria.

Russell body gastritis with Dutcher bodies evaluated using magnification endoscopy

Russell body gastritis(RBG) is an unusual type of chronic gastritis characterized by marked infiltration of Mott cells,which are plasma cells filled with spherical eosinophilic bodies referred to as Russell bodies.It was initially thought that Helicobacter pylori(H.pylori) infection was a major cause of RBG and that the infiltrating Mott cells were polyphenotypic;however,a number of cases of RBG without H.pylori infection or with monoclonal Mott cells have been reported.Thus,diagnostic difficulty exists in distinguishing RBG with monoclonal Mott cells from malignant lymphoma.Here,we report an unusual case of an 86-year-old-Japanese man with H.pylori-positive RBG.During the examination of melena,endoscopic evaluation confirmed a 13-mm whitish,flat lesion in the gastric antrum.Magnification endoscopy with narrowband imaging suggested that the lesion was most likely a poorly differentiated adenocarcinoma.Biopsy findings were consistent with chronic gastritis with many Mott cells with intranuclear inclusions referred to as Dutcher bodies.Endoscopic submucosal dissection confirmed the diagnosis of RBG with kappa-restricted monoclonal Mott cells.Malignant lymphoma was unlikely given the paucity of cytological atypia and Ki-67 immunoreactivity of monoclonal Mott cells.This is the first reported case of RBG with endoscopic diagnosis of malignant tumor and the presence of Dutcher bodies.

Image interpolation based on Wavelet Transform

Image interpolation is widely studied and used in digital image processing. In this paper, a method of image magnification according to the properties of fi＇actal interpolation and wavelet transformation are presented. We focus the development of edge forming methods to be applied as a post process of standard image zooming methods for grayscale images, with the hope of retaining edges. Experiments make sure it valid.

Image Magnification Method Using Joint Diffusion

In this paper a new algorithm for image magnification is presented. Because linear magnification/interpolation techniques diminish the contrast and produce sawtooth effects, in recent years, many nonlinear interpolation methods, especially nonlinear diffusion based approaches, have been proposed to solve these problems. Two recently proposed techniques for interpolation by diffusion, forward and backward diffusion (FAB) and level-set reconstruction (LSR), cannot enhance the contrast and smooth edges simultaneously. In this article, a novel Partial Differential Equations (PDE) based approach is presented. The contributions of the paper include: firstly, a unified form of diffusion joining FAB and LSR is constructed to have all of their virtues; secondly, to eliminate artifacts of the joint diffusion, soft constraint takes the place of hard constraint presented by LSR; thirdly, the determination of joint coefficients, criterion for stopping time and color image processing are also discussed. The results demonstrate that the method is visually and quantitatively better than Bicubic, FAB and LSR.

Edge-Aware Level Set Diffusion and Bilateral Filtering Reconstruction for Image Magnification

In this paper we propose an image magnification reconstruction method. In recent years many interpolation algorithms have been proposed for image magnification, but all of them have defects to some degree, such as jaggies and blurring. To solve these problems, we propose applying post-processing which consists of edge-aware level set diffusion and bilateral filtering. After the initial interpolation, the contours of the image are identified. Next, edge-aware level set diffusion is applied to these significant contours to remove the jaggies, followed by bilateral filtering at the same locations to reduce the blurring created by the initial interpolation and level set diffusion. These processes produce sharp contours without jaggies and preserve the details of the image. Results show that the overall RMS error of our method barely increases while the contour smoothness and sharpness are substantially improved.