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In allusion to the problem that the near infrared images of early teeth disease detection is low contract, minutiae feature isn’t evident and the images have small target gray range. So the image enhancement approach is proposed, which is disposed by the high frequency filter, linear compensation and the successive mean quantization transform. First, the near infrared images of teeth are filtered by the high frequency filter, the high frequency filter can emphasize on high-frequency components and keep lost low-frequency components, then the near infrared images are linearly compensated, finally the method combined with the successive mean quantization transform to enhance the near infrared images. The experiments show that the enhancement images show high contract and detail feature is obvious. Visually it is better to observe whether the teeth are diseased. Compared with the results of histogram equalization, the proposed method can get better enhancement effect and the particular features are stand out.

A novel adaptive aircraft detection method based on level set processing and circle-frequency filter is proposed in this paper. First, the SBGFRLS (Selective Binary and Gaussian Filtering Regularized Level Set) method is used twice to find airport region of interest (ROI) and candidate aircraft areas by local segmentation and global segmentation, respectively, so that sizes of those possible target areas can be computed. Then, the circle-frequency (CF) filter method is utilized adaptively to detect target aircrafts in the airport ROI via the mean radius estimated by sizes of those candidate areas obtained before. Experimental results on real remote sensing airport images demonstrate the efficiency and accuracy of the proposed method.

The optical model of polycrystalline networks of histological sections of rectum wall is suggested. The results of investigating the interrelation between the values of statistical (statistical moments of the 1st-4th order) parameters are presented. They characterize the coordinate distributions of the fourth parameter of Stokes vector of Fourier transforms of laser images of rectum wall histological sections and oncological changes. The diagnostic criteria of rectum cancer are determined.

In this paper, a de-striping algorithm based on adaptive frequency filter is proposed. It defines angle mapping in Log-Polar space for the satellite image to computer the approximate image rotation angle, develops the automatic effective area interception method and realizes the automatic image processing. This paper compares the algorithm results with official processing results by qualitative and quantitative evaluations. The results prove this algorithm can remove oblique stripe noises effectively in ALOS imagery and image quality improves adopting this developed de-striping algorithm.

Multiphoton excitation-induced photoacoustic microscopy (MEPAM) can be used to investigate the interior of dense objects precisely and directly because the multiphoton excitation occurs only at the focal point. This method makes it possible to avoid the strong signal from the surface of dense objects. However, in the case of tissue imaging, one-photon photoacoustic signals affect the image constructed from MEPAM signals, owing to the smaller cross section of multiphoton absorption compared with that of one-photon absorption. Thus, in order to apply MEPAM for precise investigation in living tissues, it is important to enhance (or extract) only the photoacoustic signals induced by multiphoton excitation. In this study, we examined the use of frequency-selective detection (frequency filtering) in multiphotonphotoacoustic imaging by evaluating the depth discrimination and penetration. Because MEPAM signals are generated in a very small region, they include higher frequency components compared with one-photon photoacoustic signals. We measured the images at the cross sections of blood-vessel phantoms visualized by MEPAM using the high-frequency components. We found that the images visualized using only high-frequency components showed better contrast compared with those visualized using all frequency components. We conclude that the combination of frequency filtering and MEPAM demonstrates great potential for precise observation of cross sections of blood vessels in living tissues.

A Fourier frequency filtering approach is applied to thin film design in situations well exceeding the theoretical limits of the conventional Fourier transform method. Previous work is generalized to oblique incidence. Examples of a high-reflectance filter and a broadband, wide-angle antireflection coating are given.

Human vision models have been shown to capture the response of the visual system; their incorporation into the classification stage of a Computer Aided Detection system could improve performance. This study seeks to improve the performance of an automated breast mass detection system by using the Watson filter model versus a Laguerre Gauss Channelized Hotelling Observer (LG-CHO). The LG-CHO and the Watson filter model were trained and tested on a 512x512 ROI database acquired from the Digital Database of Screening Mammography consisting of 800 total ROIs; 200 of which were malignant, 200 were benign and 400 were normal. Half of the ROIs were used to train the weights for ten LG-CHO templates that were later used during the testing stage. For the Watson filter model, the training cases were used to optimize the frequency filter parameter empirically to yield the best ROC Az performance. This set of filter parameters was then tested on the remaining cases. The training Az for the LG-CHO and the Watson filter was 0.896 +/- 0.016 and 0.924 +/- 0.014 respectively. The testing Az for the LG-CHO and Watson filter was 0.849 +/- 0.019 and 0.888 +/- 0.017. With a p-value of 0.029, the difference in testing performance was statistically significant, thus implying that the Watson filter model holds promise for better detection of masses.

This paper presents a new approach to detect airplanes in panchromatic remote-sensing images. A circle-frequency filter(CF- filter) is given to locate airplane centers from the background. The filter extracts candidate points of airplane centers first. Then through a simple clustering method, airplane centers can be located. 8 panchromatic images of 1.0m~4.0m resolution, including 65 airplanes, are tested with this approach. 59 airplanes are detected and 5 times are false alarmed.

This paper discusses Moise cable transmitters' manual dexterity differences using pattern recognition. Firstly, using amplitude and frequency filtering of the frequency sampling voice signals results in the extraction of the characteristics of demodulated base band signal. Secondly, the calculation of the minimum space distance allows recognition of the manual techniques differences of Moise cable transmitters.

A new, very simple AR coating synthesis method is further developed and compared to a recent `quasi-optimal' technique. A remarkable resemblance is found in the results. The reason for this similarity is given and the performance of both approaches is discussed.

In optical information processing polarization and color may be introduced as orthogonal states in established measuring techniques. These signal independent states offer a great flexibility in information processing as for example frequency filtering in the space domain.

Frequency-domain analysis offers several advantages when considering surface profile measurements. Vibration of the sample during the measurement is often clearly defined in the profile frequency spectrum and its effect on the measured data can be reduced by an appropriate filter. The finish of surfaces with periodic height variations (such as diffraction gratings) can be measured if the periodic structure is first removed. This paper examines the application of frequency filtering techniques to these problems.