In the field of photography measurement, parameterized models are usually established to account for lens distortions, such as the radial, tangential, affine, and nonorthogonality deformations. However, all of these models are the approximations of the realistic model of lenses, instead since some distortions cannot be parameterized accurately. This restricts the improvement of measuring accuracy. Moreover, the nonlinear minimization, which has been widely used with the pin-hole model and lens distortion model coupled, always converges to local solution because of the correlation of the parameters in the two models. Several researchers have proposed generic nonparametric idea, which can be applied equally well to all types of cameras, but the accuracy cannot meet the requirement of close-range photogrammetry. So an optical calibration method based on nonparametric ideas is proposed to find the mapping between incoming scene rays and image points, and subpixel image processing was used to position the image points. It is applicable to a central (single viewpoint) camera equipped with any lenses. This method is applied to the stereoscopic system, and the results show a good measuring accuracy.
A wavelength encoded optical fiber sensor using a three-segmented fiber structure is proposed. The device consists of a
coreless silica fiber (CSF) which is coated with a thin film and spliced between two standard single-mode fibers (SMFs),
forming a SMF-CSF-SMF (SCS) structure. When light is transmitted from the SMF into the CSF, the LP01 mode in the
SMF is coupled to the LP0n modes, and a multimode interference occurs in the CSF. These modes interact with the thin
film, hence the thickness and refractive index of the thin film can affect the modal interference. We analyze the
transmission spectra of the SCS structure to obtain the characteristics of the sensor including sensing sensitivity.
Numerical simulations are carried out by using the Beam Propagation Method (BPM) to investigate the multimode
interference in the SCS. Two different conditions are considered in our studies: 1) changing the refractive index of a
fixed-thickness film, and 2) varying the film thickness with certain refractive index. It has been found that the
wavelength corresponding to the minimum output power increases 0.33509 nm when the refractive index changes every
0.01 from 1.33 up to 1.40, and 6.760 nm when the thickness enhances form 0 to 1000 nm. The trend of the raise is
mostly linear for the former simulation, but gets slower and slower for the latter. The SCS structure can serve as a fiber
platform for non-labeling bio-sensing when a bio-film is coated to the CSF.
This paper proposes a new image super-resolution restoration algorithm. The development of the algorithm is based on the improvement of the classical projection on convex set (POCS) algorithm and wavelet fusion to restore a super-resolution image from a series of low resolution (LR) images. At first, the POCS iteration is used to restore high-resolution (HR) image from every LR image. Then several different rules are chosen to fuse HR images in wavelet domain, and a HR image is reconstructed by inverse wavelet transform. The reconstructed image is evaluated by entropy, cross entropy, definition and the peak signal-noise ratio. The experimental results of the processed CT images showed that this method can improve the ability of fusing different image information, and the texture of the image is more prominent, the image quality is higher.