scholarly journals RESEARCH OF DIGITAL CAMERA DYNAMIC RANGE ON THE IMAGING PROCESSING BASIS

2017 ◽  
Vol 8 (3) ◽  
pp. 271-278
Author(s):  
M Sutkowski ◽  
Ya. N. Saukova
Keyword(s):  
Dynamic Range ◽  
Digital Camera ◽  
Measuring Channel ◽  
Blue Color ◽  
Lower And Upper Bounds ◽  
Color Target ◽  
Color Channel ◽  
Imaging Processing ◽  
Colorimetric Measurements ◽  
Target Sets

Digital images provide to determine photometric and colorimetric properties of objects subject to validation all elements of a measuring channel (digital camera, software, display) and solve the problem of their limited dynamic ranges. The aim of the study was to explore the dynamic range of a digital camera for use in photometric and colorimetric measurements.The Laboratory of Photonics at the Institute of Microelectronics and Optoelectronics (Warsaw Technical University, Poland) conducted a comparative experiment to determine the threshold of sensitivity, linearity and range of application the digital camera. Color target sets with certified brightness and chromaticity were created at the terminals and recorded with a digital camera with different exposure times. The authors propose a method to extend the dynamic range of a digital camera for red, green and blue color channel of intensities by pairing the calibration dependencies, and determine the true brightness and color of a point on the object by calculation.Calibration dependencies (triads) of digital camera for red, green and blue color channels intensities were constructed. These dependences allow determining lower and upper bounds of the dynamic range. Each triad has a form of the hysteresis loop. The experiment showed that the accuracy of this method is ± 3–5 %. 

Large Area, Full-Color Image Sensors Made with Organic Semiconductors

1999 ◽  
Vol 558 ◽  
Author(s):  
G. Yu ◽  
G. Srdanov ◽  
J. Wang ◽  
A.J. Heeger
Keyword(s):  
Dark Current ◽  
Dynamic Range ◽  
Color Image ◽  
Sensor Arrays ◽  
Blue Color ◽  
Two Dimensional ◽  
Large Area ◽  
Full Color ◽  
Sensing Applications ◽  
Photodiode Arrays

ABSTRACTLarge area polymer photodiode arrays were designed and fabricated for full-color imaging applications. These sensor arrays are of high photosensitivity, low dark current, large dynamic range and fast response time. The red, green and blue color primaries were achieved by coupling a set of color filters with the polymer sensor pixels with broad response covering entire visible spectrum. Image recovery process from the pixel photocurrent data was developed, which is suitable generally to image arrays with power-law light intensity dependence and with finite pixel dark current. Large sensing length photodiode arrays (2.5”5”) were fabricated with pixel densities from 40 to 100 dot-per-inch. They were used as the sensing elements in page size document scanners. Voltage switchable polymer photodetectors were developed. Their photosensitivity can be switched on and off with external bias. These devices can be used as the sensing elements in x-y addressable two-dimensional sensor matrices. The high on/off switching ratio and high photocurrent/dark-current ratio allow such two-dimensional, passive photosensor matrices be used for image sensing applications.

scholarly journals URGENCY OF USING HIDDEN DATA TRANSMISSION IN VIDEO FILES

2021 ◽  
pp. 48-54
Author(s):  
Yevheniia Kataieva ◽  
Anton Rebrikov
Keyword(s):  
Digital Media ◽  
Data Transmission ◽  
Digital Processing ◽  
Digital Data ◽  
Blue Color ◽  
Color Channel ◽  
Video Steganography ◽  
Advantages And Disadvantages ◽  
The Subject ◽  
Hidden Data

The article examines the problems of protecting information from unwanted access, which have tried to solve throughout the existence of mankind. Nowadays, the widespread use of electronic means of communication, electronic eavesdropping and fraud, a variety of computer viruses and other electronic hazards, electronic systems place high demands on the protection of information. Thus, the study of digital steganography is an urgent task. There are two main areas of hidden data transmission: cryptography and steganography. The purpose of cryptography is to restrict access to information by encrypting it. Unlike cryptography, steganography allows you to hide the very fact of the presence of hidden data. The study examined the main methods of covert data transmission using computer steganography, namely: the method of using system-reserved areas of digital data formats, methods of hiding information by special formatting of text files, which include the use of word, sentence or paragraph shift, selection certain positions of letters in the text or the use of properties of system fields that are not displayed on the screen, the method of using simulation functions, methods of using unused disk sectors, the method of using redundant media files (audio, photo and video). Currently, due to the growth of information and increasing the bandwidth of communication channels, the issue of hiding information in video sequences is becoming increasingly important. The transmission of digital video in recent years is a typical event and does not arouse suspicion. In the course of the research the peculiarities of hiding information in video files are considered, the comparison of existing algorithms of computer video steganography is made. The task is to develop your own algorithm for embedding information in the blue color channel of video files. The object of research is the transfer of hidden data in digital media files. The subject of research is the transmission of hidden data in the video stream. The purpose of research is to review the subject area, to examine the available methods of embedding information in media files in general and specifically in video files, to identify the advantages and disadvantages of existing algorithms, to develop their own algorithm of video steganography based on previously obtained research results. Research methods - methods of information theory, probability theory and mathematical statistics; methods of digital processing of signals, static images and video files; methods of vector analysis. The results of research - an overview of the features of hiding information in video files, compared existing algorithms of computer video steganography.

A Color Error Correction Mode for Digital Camera

2010 ◽  
Vol 44-47 ◽  
pp. 3706-3710
Author(s):  
Han Kun Ye
Keyword(s):  
Color Space ◽  
Digital Camera ◽  
Color Management ◽  
Experimental Sample ◽  
Color Target ◽  
Polynomial Curve ◽  
Engineering Requirement ◽  
Color Error ◽  
Image Production ◽  
Color Conversion

Digital camera is the one of the main devices in the computer and multimedia technology and its color management model is the key to guarantee the color consistency in the succedent image production and transfers. The paper presents a color conversion model for digital camera based on polynomial curve generation. First, color rendering principle of digital camera is analyzed. Then digital camera data is pretreated to a unitary field to deduce final model. Third, standard color target is taken for experimental sample and substitutes color blocks in color shade district for complete color space to solve the difficulties of experimental color blocks selecting; Fourth, the model using polynomial curve generation algorithm to correct color error is deduced; Finally, the realization and experiment results show that, compared with some methods which have relatively high accuracy, the algorithm can improve color conversion accuracy and can satisfy the engineering requirement in digital camera color management

scholarly journals Retinex-Based Fast Algorithm for Low-Light Image Enhancement

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 746
Author(s):  
Shouxin Liu ◽  
Wei Long ◽  
Lei He ◽  
Yanyan Li ◽  
Wei Ding
Keyword(s):  
Image Enhancement ◽  
Fast Algorithm ◽  
Dynamic Range ◽  
Color Space ◽  
Mapping Function ◽  
Blue Color ◽  
Gray Level ◽  
Low Light ◽  
Light Image ◽  
Adaptive Gamma Correction

We proposed the Retinex-based fast algorithm (RBFA) to achieve low-light image enhancement in this paper, which can restore information that is covered by low illuminance. The proposed algorithm consists of the following parts. Firstly, we convert the low-light image from the RGB (red, green, blue) color space to the HSV (hue, saturation, value) color space and use the linear function to stretch the original gray level dynamic range of the V component. Then, we estimate the illumination image via adaptive gamma correction and use the Retinex model to achieve the brightness enhancement. After that, we further stretch the gray level dynamic range to avoid low image contrast. Finally, we design another mapping function to achieve color saturation correction and convert the enhanced image from the HSV color space to the RGB color space after which we can obtain the clear image. The experimental results show that the enhanced images with the proposed method have better qualitative and quantitative evaluations and lower computational complexity than other state-of-the-art methods.

Practical Methods for Characterizing the Optical Performance of Digital Camera-Based Imaging Systems

2020 ◽  
Vol 9 (1) ◽  
pp. 31-45
Author(s):  
Sami D. Alaruri
Keyword(s):  
Optical System ◽  
Dynamic Range ◽  
Visible Region ◽  
Digital Camera ◽  
Ccd Camera ◽  
Integrating Sphere ◽  
Test Target ◽  
Optical Performance ◽  
Modulation Transfer ◽  
Halogen Light

In this paper, practical and simple methods for characterizing the optical performance of a digital CCD camera equipped with a zoom lens using test targets projected by a Newtonian collimator coupled to an integrating sphere and a halogen light source are presented. The presented methods include the evaluation of the CCD camera system modulation transfer function (MTF), uniformity, dynamic range, linearity, and signal-to-noise ratio (S/N) properties in the visible region of the spectrum. Through out this work image processing for the recorded target images is performed using ImageJ. In addition, the paper presents a comparison between MTF measurements collected with a 1951-USAF resolution test target and a slanted edge test target. Finally, simple mathematical expressions for the measured optical system performance properties are provided. The presented optical system characterization methods can provide researchers with the needed data when a CCD or CMOS digital camera is integrated with a lens system.

FACEMASK RECOGNITION IN PANDEMIC CAUSES MULTIPLE HEAD CRUCIAL PROBLEM CLASSIFICATION

2021 ◽  
Vol 5 (10) ◽  
Author(s):  
Sushma Kumari
Keyword(s):  
Neural Networks ◽  
High Speed ◽  
Color Space ◽  
Research Paper ◽  
Blue Color ◽  
Facial Image ◽  
Color Channel ◽  
Convolution Neural Networks ◽  
Fine Grained ◽  
Crucial Problem

—A chronicle respiratory system condition like Breathing issues to Asthma patients after covering his/her mouth and nose make a tough challenge. Mainly the physical barrier are to take breath in oxygen, it also pack CO2 which the person exhale. A mask can feel high suffocation and add a compromised Head crucial problem stratification is in general used for the fore handling ahead of the facial acknowledgement & facial several inclination issues and only for this reason an algorithm like recognition of front facial expressions as a input images. However pretentious by Corona virus epidemic, public put on face masks to safe ourselves safety, for that face will protected by mask. However this research paper set up a proposed method in this research paper of combining the face portrait with the High speed - channel of the Hue Saturation Value color channel and grayscale image, and train the Convolution Neural Networks to enhance applications that is HGL method. In line portrait we have to generate the image insert it into Convolution Neural Networks for training. Without any processing insert the original picture of the Red Green Blue color space into the Convolution Neural Networks. Fine grained Net Structured Aggregation: FSA – NET stand for Fine grained Structured Aggregation. It is the method to use to remember the structure of a single Red Green Blue color space image. Since the output of this network is the Euler angle of the head pose, we have chosen a set of thresholds that are most effective for pose classification. The way to solve this issue is to provide help for the study of multi-angle problems. In practically, we can practice for a face detection algorithm that differentiate between wearing a mask or demask. If the facial image with masks, we can recommend this method proposed in this paper, and if it is a normal facial image, we can recommend Fine grained Structured Aggregation or Line Portrait algorithm, etc. The very first step of this algorithm to res

Sign in / Sign up

Export Citation Format

Share Document