scholarly journals The Nature of Radio Interference and Some Lines of Defense

1991 ◽  
Vol 112 ◽  
pp. 240-248
Author(s):  
J. Richard Fisher
Keyword(s):  
Radio Astronomy ◽  
Dynamic Range ◽  
State Of The Art ◽  
High Dynamic Range ◽  
Radio Spectrum ◽  
The State ◽  
Radio Interference ◽  
Frequency Bands ◽  
High Dynamic ◽  
Technical Effort

ABSTRACTAs competition for radio spectrum space continues to increase, radio astronomers can expect to put more technical effort into ways of observing in the presence of interference. Much of the spectrum outside of exclusive radio astronomy frequency bands will continue to be available to the science if receivers and antennas are designed to make efficient use of times, frequencies, directions, and coherence envelopes that do not contain sources of interference. The paper outlines the state of the art in antenna sidelobe reduction, high dynamic range spectrometers, and receiver designs for handling large signals. Techniques for excising pulsed interference on very short timescales and a few thoughts on signal canceling techniques are discussed.

scholarly journals Use of an Occlusion Mask for Veiling Glare Removal in HDR Images

2018 ◽  
Vol 4 (8) ◽  
pp. 100
Author(s):  
Federico Cozzi ◽  
Carmine Elia ◽  
Giovanni Gerosa ◽  
Filippo Rocchetta ◽  
Matteo Lanaro ◽  
...  
Keyword(s):  
Dynamic Range ◽  
State Of The Art ◽  
High Dynamic Range ◽  
The State ◽  
Optical Systems ◽  
Range Images ◽  
Digital Cameras ◽  
Acquisition Process ◽  
High Dynamic ◽  
Post Production

Optical systems in digital cameras present a limit during the acquisition of standard and High Dynamic Range Images (HDRI) due to the presence of veiling glare, an artifact caused by an unwanted spread of the source of light. In this paper, we analyze the state-of-the-art of veiling glare removal in HDRI, giving attention to the paper presented by Talvala. Then we describe an algorithm for veiling glare removal based on the same occlusion mask, to study the benefits provided by it in HDRI acquisition process. Finally, we demonstrate the efficiency of the occlusion mask method in veiling glare removal without any post production estimation and subtraction.

scholarly journals State-of-the-art VLBI imaging: 3C345

1991 ◽  
Vol 131 ◽  
pp. 354-357
Author(s):  
Ann E. Wehrle ◽  
Stephen C. Unwin
Keyword(s):  
Thermal Noise ◽  
Dynamic Range ◽  
State Of The Art ◽  
High Dynamic Range ◽  
Instrumental Effects ◽  
High Dynamic ◽  
Low Dynamic Range ◽  
Very High

AbstractMost VLBI images have low dynamic range because they are limited by instrumental effects such as calibration errors and poor u, v-coverage. We outline the method used to make a new image of the bright quasar 3C345 which has very high dynamic range (peak-to-noise of 5000:1) and which is limited by the thermal noise, not instrumental errors. Both the Caltech VLBI package and the NRAO AIPS package were required to manipulate the data.

scholarly journals K-means clustering based tone-mapping operator for high dynamic range video

2021 ◽  
Author(s):  
Negar Taherian
Keyword(s):  
Clustering Algorithm ◽  
Dynamic Range ◽  
State Of The Art ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Scene Change Detection ◽  
Mapping Algorithms ◽  
Mapping Algorithm ◽  
High Dynamic ◽  
Video Input

The field of high dynamic range (HDR) imaging deals with capturing the luminance of a natural scene, usually varying between 10−3 to 105 cd/m2 and displaying it on digital devices with much lower dynamic range. Here, we present a novel tone mapping algorithm that is based on K-means clustering. Our algorithm takes into account the color information within a frame and using k-means clustering algorithm it builds clusters on the intensities within an image and shifts the values within each cluster to a displayable dynamic range. We also implement a scene change detection to reduce the running time of our algorithm by using the cluster information from the previous frame for frames within the same scene. To reduce the flicker effect, we proposed a new method that multiplies a leaky integer to the centroid values of our clustering results. Our algorithm runs in O( N logK + K logK ) for an image with N input luminance levels and K output levels. We also show how to extend the method to handle video input. We display that our algorithm gives comparable results to state-of-the- art tone mapping algorithms. We test our algorithm on a number of standard high dynamic range images and video sequences and provide qualitative and quantitative comparisons to a number of state-of-the-art tone mapping algorithms for videos.

scholarly journals A Deep Learning Approach in the DCT Domain to Detect the Source of HDR Images

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2053
Author(s):  
Jiayu Wang ◽  
Hongquan Wang ◽  
Xinshan Zhu ◽  
Pengwei Zhou
Keyword(s):  
Discrete Cosine Transform ◽  
Dynamic Range ◽  
State Of The Art ◽  
High Dynamic Range ◽  
Cosine Transform ◽  
Spatial Image ◽  
Multi Scale ◽  
Dct Domain ◽  
High Dynamic ◽  
Fully Connected

Although high dynamic range (HDR) is now a common format of digital images, limited work has been done for HDR source forensics. This paper presents a method based on a convolutional neural network (CNN) to detect the source of HDR images, which is built in the discrete cosine transform (DCT) domain. Specifically, the input spatial image is converted into DCT domain with discrete cosine transform. Then, an adaptive multi-scale convolutional (AMSC) layer extracts features related to HDR source forensics from different scales. The features extracted by AMSC are further processed by two convolutional layers with pooling and batch normalization operations. Finally, classification is conducted by a fully connected layer with Softmax function. Experimental results indicate that the proposed DCT-CNN outperforms the state-of-the-art schemes, especially in accuracy, robustness, and adaptability.

scholarly journals K-means clustering based tone-mapping operator for high dynamic range video

2021 ◽  
Author(s):  
Negar Taherian
Keyword(s):  
Clustering Algorithm ◽  
Dynamic Range ◽  
State Of The Art ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Scene Change Detection ◽  
Mapping Algorithms ◽  
Mapping Algorithm ◽  
High Dynamic ◽  
Video Input

The field of high dynamic range (HDR) imaging deals with capturing the luminance of a natural scene, usually varying between 10−3 to 105 cd/m2 and displaying it on digital devices with much lower dynamic range. Here, we present a novel tone mapping algorithm that is based on K-means clustering. Our algorithm takes into account the color information within a frame and using k-means clustering algorithm it builds clusters on the intensities within an image and shifts the values within each cluster to a displayable dynamic range. We also implement a scene change detection to reduce the running time of our algorithm by using the cluster information from the previous frame for frames within the same scene. To reduce the flicker effect, we proposed a new method that multiplies a leaky integer to the centroid values of our clustering results. Our algorithm runs in O( N logK + K logK ) for an image with N input luminance levels and K output levels. We also show how to extend the method to handle video input. We display that our algorithm gives comparable results to state-of-the- art tone mapping algorithms. We test our algorithm on a number of standard high dynamic range images and video sequences and provide qualitative and quantitative comparisons to a number of state-of-the-art tone mapping algorithms for videos.

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