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

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.

1991 ◽  
Vol 131 ◽  
pp. 354-357
Author(s):  
Ann E. Wehrle ◽  
Stephen C. Unwin

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.


2021 ◽  
Author(s):  
Negar Taherian

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.


Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 24
Author(s):  
Yan-Tsung Peng ◽  
He-Hao Liao ◽  
Ching-Fu Chen

In contrast to conventional digital images, high-dynamic-range (HDR) images have a broader range of intensity between the darkest and brightest regions to capture more details in a scene. Such images are produced by fusing images with different exposure values (EVs) for the same scene. Most existing multi-scale exposure fusion (MEF) algorithms assume that the input images are multi-exposed with small EV intervals. However, thanks to emerging spatially multiplexed exposure technology that can capture an image pair of short and long exposure simultaneously, it is essential to deal with two-exposure image fusion. To bring out more well-exposed contents, we generate a more helpful intermediate virtual image for fusion using the proposed Optimized Adaptive Gamma Correction (OAGC) to have better contrast, saturation, and well-exposedness. Fusing the input images with the enhanced virtual image works well even though both inputs are underexposed or overexposed, which other state-of-the-art fusion methods could not handle. The experimental results show that our method performs favorably against other state-of-the-art image fusion methods in generating high-quality fusion results.


1991 ◽  
Vol 112 ◽  
pp. 240-248
Author(s):  
J. Richard Fisher

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.


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