Night vision

About: Night vision is a research topic. Over the lifetime, 6004 publications have been published within this topic receiving 67372 citations.

Computer Vision and Image Processing: A Practical Approach Using CVIPTools

Abstract: I. COMPUTER VISION AND IMAGE PROCESSING FUNDAMENTALS. 1. Introduction to Computer Vision and Image Processing. Overview: Computer Imaging. Computer Vision. Image Processing. Computer Imaging Systems. The CVIPtools Software. Human Visual Perception. Image Representation. Digital Image File Formats. References. 2. Image Analysis. Introduction. Preprocessing. Edge/Line Detection. Segmentation. Discrete Transforms. Feature Extraction and Analysis. References. 3. Image Restoration. Introduction. Noise. Noise Removal Using Spatial Filters. Frequency Domain Filters. Geometric Transforms. References. 4. Image Enhancement. Introduction. Gray-Scale Modification. Image Sharpening. Image Smoothing. References. 5. Image Compression. Introduction. Lossless Compression Methods. Lossy Compression Methods. References. II. CVIPtools. 6. Using CVIPtools. Introduction and Overview. The Graphical User Interface. Examples. 7. CVIPtools Applications. Introduction. Automatic Skin Tumor Border Identification. Helicopter Image Enhancement and Analysis. Wavelet/Vector Quantization Compression. Image Segmentation Using a Deformable Template Algorithm. Visual Acuity/Night Vision Simulation. 8. Programming with CVIPtools. Introduction to CVIPlab. CVIP Laboratory Exercises. The CVIPtcl and CVIPwish Shells. 9. CVIPtools Library Functions. Introduction. Arithmetic and Logic Library_libarithlogic. Band Image Library_libband. Color Image Library_libcolor. Compression Library_libcompress. Conversion Library_libconverter. Display Library_libdisplay. Feature Extraction Library_libfeature. Geometry Library_libgeometry. Histogram Library_libhisto. Image Library_libimage. Data Mapping Library_libmap. Morphological Library_libmorph. Noise Library_libnoise. Segmentation Library_libsegment. Spatial Filter Library_libspatialfilter. Transform Library_libtransform. III. APPENDICES. A. The CVIPtools CD-ROM. B. Setting Up and Updating Your CVIPtools Environment. Getting CVIPtools software updates. To get via the WWW. C. CVIPtools Functions. Toolkit Libraries. Toolbox Libraries. D. CVIPtcl Command List and Corresponding CVIPtools Functions. E. CVIPtcl Function Usage Notes. F. CVIP Resources. Index.

Poisson Noise Reduction with Non-local PCA

Abstract: Photon-limited imaging arises when the number of photons collected by a sensor array is small relative to the number of detector elements. Photon limitations are an important concern for many applications such as spectral imaging, night vision, nuclear medicine, and astronomy. Typically a Poisson distribution is used to model these observations, and the inherent heteroscedasticity of the data combined with standard noise removal methods yields significant artifacts. This paper introduces a novel denoising algorithm for photon-limited images which combines elements of dictionary learning and sparse patch-based representations of images. The method employs both an adaptation of Principal Component Analysis (PCA) for Poisson noise and recently developed sparsity-regularized convex optimization algorithms for photon-limited images. A comprehensive empirical evaluation of the proposed method helps characterize the performance of this approach relative to other state-of-the-art denoising methods. The results reveal that, despite its conceptual simplicity, Poisson PCA-based denoising appears to be highly competitive in very low light regimes.

Pedestrian Detection usingInfraredimages and Histograms of Oriented Gradients

Abstract: Thispaperpresents acomplete methodforpedes- trian detection applied toinfrared images. First, westudy an imagedescriptor basedonhistograms oforiented gradients (HOG),associated witha Support Vector Machine(SVM) classifier andevaluate itsefficiency. Afterhaving tunedthe HOG descriptor andtheclassifier, weinclude this methodin acomplete system, whichdeals withstereo infrared images. Thisapproach gives goodresults forwindowclassification, andapreliminary testapplied onavideosequence proves thatthis approach isverypromising. I.INTRODUCTION Since thelast fewyears now,thedevelopment ofdriving assistance systems hasbeenveryactive inorder toin- crease thevehicle anditsenvironment safety. Atthe present time, themainobjective inthisdomainisto provide thedrivers withsomeinformation concerning its environment andanypotential hazard. Oneamongall useful information isthedetection andlocalization ofa pedestrian infront ofavehicle. Thisproblem ofdetecting pedestrians isaverydifficult problemthathasessentially beenaddressed using vision sensors, imageprocessing andpattern recognition techniques. Inparticular, detecting pedestrians thanks to images isacomplex challenge duetotheir appearance andposevariability. Inthecontext ofdaylight vision, several approaches havebeenproposed andarebased on different imageprocessing techniques ormachine learning (9), (5), (12). Recently, owingtothedevelopment oflow-cost infrared cameras, night vision systems havegained moreand moreinterest, thusincreasing theneedofautomatic detection ofpedestrians atnight. Thisproblem of detecting pedestrians frominfrared images hasbeen investigated byvarious research teamsinthelast years. Themainmethodology isbasedon extracting cues (symmetry, shape-independent

Effect of pupillary dilation on corneal optical aberrations after Photorefractive keratectomy

Abstract: Background: Complaints of glare, halos, and disturbances of night vision after photorefractive keratectomy (PRK) probably result from changes in the corneal aberration structure induced by the laser ablation procedure. The purpose of this article is to characterize changes in the corneal aberration structure after PRK and to demonstrate the effect of pupil dilation on these changes. Methods: Videokeratographs obtained preoperatively (n = 112) and at 1 (n = 94), 3 (n = 103), 6 (n = 91), 12 (n = 60), 18 (n = 53), and 24 (n = 44) months postoperatively from 112 eyes of 89 patients who had undergone PRK for myopia were analyzed. The data were used to calculate the wavefront variance of the cornea for both small (3-mm) and large (7-mm) pupils. Results: For both the 3- and 7-mm pupil, coma-like aberrations increased significantly from preoperative values to 1-month postoperative values (P,.05 and P,.001, respectively); for 7-mm pupils, the postoperative values never returned to preoperative values (P,.001, 24 months). For the 3-mm pupil, spherical-like aberrations decreased significantly 1 month after surgery (P,.001), and never returned to preoperative values. For the 7-mm pupil, spherical-like aberrations increased significantly 1 month after surgery (P,.001) and did not return to preoperative values. Opening the pupil from 3 to 7 mm increased spherical-like aberrations only 7-fold before PRK. After PRK, however, pupillary dilation caused a 300-fold increase in this type of aberration. For both pupil sizes at all times after PRK, the magnitude of the surgically induced aberration correlated with the amount of the attempted correction (P,.001, r 2 = 0.6 at 1 month for a 7-mm pupil). Conclusions: Photorefractive keratectomy increases the wavefront variance of the cornea; PRK changes the relative contribution of coma-like and spherical-like aberrations; after PRK, the diameter of the entrance pupil greatly affects the amount and character of the aberrations; and the magnitude of the aberration increases with the attempted correction. Clinical Relevance: Quantitative characterization of irregular astigmatism with the measurement of aberration structures following corneal surgery and the correlation of these data with visual performance in clinical trials provide the basis for understanding patient complaints and for improving surgical approaches. Our analysis shows that, whereas induced aberrations are minimal for simulated daytime vision (3-mm pupil), the increase in aberrations measured for simulated night vision (7-mm pupil) supports the use of large treatment zones to reduce visual disturbances such as glare and halos.