scholarly journals A Novel Zero Watermarking Based on DT-CWT and Quaternion for HDR Image

Electronics ◽  
2021 ◽  
Vol 10 (19) ◽  
pp. 2385
Author(s):  
Jiangtao Huang ◽  
Shanshan Shi ◽  
Zhouyan He ◽  
Ting Luo
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Complex Wavelet Transform ◽  
Color Channel ◽  
Low Pass ◽  
Zero Watermarking ◽  
Contour Change ◽  
Value Decomposition ◽  
Hdr Image ◽  
Color Channels

This paper presents a high dynamic range (HDR) image zero watermarking method based on dual tree complex wavelet transform (DT-CWT) and quaternion. In order to be against tone mapping (TM), DT-CWT is used to transform the three RGB color channels of the HDR image for obtaining the low-pass sub-bands, respectively, since DT-CWT can extract the contour of the HDR image and the contour change of the HDR image is small after TM. The HDR image provides a wide dynamic range, and thus, three-color channel correlations are higher than inner-relationships and the quaternion is used to consider three color channels as a whole to be transformed. Quaternion fast Fourier transform (QFFT) and quaternion singular value decomposition (QSVD) are utilized to decompose the HDR image for obtaining robust features, which is fused with a binary watermark to generate a zero watermark for copyright protection. Furthermore, the binary watermark is scrambled for the security by using the Arnold transform. Experimental results denote that the proposed zero-watermarking method is robust to TM and other image processing attacks, and can protect the HDR image efficiently.

scholarly journals Relative sky radiance from multi-exposure all-sky camera images

2021 ◽  
Vol 14 (3) ◽  
pp. 2201-2217
Author(s):  
Juan C. Antuña-Sánchez ◽  
Roberto Román ◽  
Victoria E. Cachorro ◽  
Carlos Toledano ◽  
César López ◽  
...  
Keyword(s):  
Dynamic Range ◽  
Quality Criteria ◽  
High Dynamic Range ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
High Dynamic ◽  
Sky Radiance ◽  
Black Level ◽  
Hdr Image

Abstract. All-sky cameras are frequently used to detect cloud cover; however, this work explores the use of these instruments for the more complex purpose of extracting relative sky radiances. An all-sky camera (SONA202-NF model) with three colour filters narrower than usual for this kind of cameras is configured to capture raw images at seven exposure times. A detailed camera characterization of the black level, readout noise, hot pixels and linear response is carried out. A methodology is proposed to obtain a linear high dynamic range (HDR) image and its uncertainty, which represents the relative sky radiance (in arbitrary units) maps at three effective wavelengths. The relative sky radiances are extracted from these maps and normalized by dividing every radiance of one channel by the sum of all radiances at this channel. Then, the normalized radiances are compared with the sky radiance measured at different sky points by a sun and sky photometer belonging to the Aerosol Robotic Network (AERONET). The camera radiances correlate with photometer ones except for scattering angles below 10∘, which is probably due to some light reflections on the fisheye lens and camera dome. Camera and photometer wavelengths are not coincident; hence, camera radiances are also compared with sky radiances simulated by a radiative transfer model at the same camera effective wavelengths. This comparison reveals an uncertainty on the normalized camera radiances of about 3.3 %, 4.3 % and 5.3 % for 467, 536 and 605 nm, respectively, if specific quality criteria are applied.

High Dynamic Range (HDR) Image Quality Assessment: A Survey

2019 ◽  
Author(s):  
Irwan Prasetya Gunawan ◽  
Ocarina Cloramidina ◽  
Salmaa Badriatu Syafa'ah ◽  
Guson Prasamuarso Kuntarto ◽  
Berkah I Santoso
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
High Dynamic ◽  
Hdr Image

scholarly journals Relative sky radiance from multi-exposure all-sky camera images

2020 ◽  
Author(s):  
Juan C. Antuña-Sánchez ◽  
Roberto Román ◽  
Victoria E. Cachorro ◽  
Carlos Toledano ◽  
César López ◽  
...  
Keyword(s):  
Dynamic Range ◽  
Quality Criteria ◽  
High Dynamic Range ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
High Dynamic ◽  
Sky Radiance ◽  
Black Level ◽  
Hdr Image

Abstract. All-sky cameras are frequently used to detect cloud cover; however, this work explores the use of these instruments for the more complex purpose of extracting relative sky radiances. An all-sky camera (SONA202-NF model) with three colour filters, narrower than usual for this kind of cameras, is configured to capture raw images at seven exposure times. A detailed camera characterization of the black level, readout noise, hot pixels and linear response is carried out. A methodology is proposed to obtain a linear high dynamic range (HDR) image and its uncertainty, which represents the relative sky radiance map at three effective wavelengths. The relative sky radiance (normalized by the sum of all radiances) is extracted from these maps and compared with the sky radiance measured at different sky points by a sun/sky photometer belonging to the Aerosol Robotic Network (AERONET). The camera radiances are in line with photometer ones excepting for scattering angles below 10º, which is probably due to some light reflections on the fisheye lens and camera dome. Camera and photometer wavelengths are not coincident, hence camera radiances are also compared with sky radiances simulated by a radiative transfer model at the same camera effective wavelengths. This comparison reveals an uncertainty on the normalized camera radiances about 3.3 %, 4.3 % and 5.3 % for 467, 536 and 605 nm, respectively, if specific quality criteria are applied.

scholarly journals A high dynamic range imaging algorithm: implementation and evaluation

2019 ◽  
Vol 22 (3) ◽  
pp. 293-307
Author(s):  
Vu Hong Son
Keyword(s):  
Exposure Time ◽  
Dynamic Range ◽  
Weighting Function ◽  
High Dynamic Range ◽  
Image Sensors ◽  
Current Image ◽  
High Dynamic ◽  
Low Dynamic Range ◽  
Algorithm Implementation ◽  
Hdr Image

Camera specifications have become smaller and smaller, accompanied with great strides in technology and thinner product demands, which have led to some challenges and problems. One of those problems is that the image quality is reduced at the same time. The decrement of radius lens is also a cause leading to the sensor not absorbing a sufficient amount of light, resulting in captured images which include more noise. Moreover, current image sensors cannot preserve whole dynamic range in the real world. This paper proposes a Histogram Based Exposure Time Selection (HBETS) method to automatically adjust the proper exposure time of each lens for different scenes. In order to guarantee at least two valid reference values for High Dynamic Range (HDR) image processing, we adopt the proposed weighting function that restrains random distributed noise caused by micro-lens and produces a high quality HDR image. In addition, an integrated tone mapping methodology, which keeps all details in bright and dark parts when compressing the HDR image to Low Dynamic Range (LDR) image for display on monitors, is also proposed. Eventually, we implement the entire system on Adlink MXC-6300 platform that can reach 10 fps to demonstrate the feasibility of the proposed technology.  

scholarly journals A Compressed Equivalent Source Method Based on Equivalent Redundant Dictionary for Sound Field Reconstruction

2019 ◽  
Vol 9 (4) ◽  
pp. 808 ◽  
Author(s):  
Yansong He ◽  
Liangsong Chen ◽  
Zhongming Xu ◽  
Zhifei Zhang
Keyword(s):  
Dynamic Range ◽  
Sound Field ◽  
High Dynamic Range ◽  
Redundant Dictionary ◽  
Equivalent Source ◽  
Practical Applications ◽  
Field Reconstruction ◽  
Source Method ◽  
Value Decomposition ◽  
Equivalent Source Method

The equivalent source method (ESM) based on compressive sensing (CS) requires that the source has a sparse or approximately sparse representation in a suitable basis or dictionary. However, in practical applications, it is not easy to find the appropriate basis or dictionary due to the indeterminate characteristics of the source. To solve this problem, an equivalent redundant dictionary is constructed, which contains two core parts: one is the equivalent dictionary used in the CS-based ESMs under the sparse assumption, and the other one is the orthogonal basis obtained by the singular value decomposition (SVD). On this foundation, a method named compressed ESM based on the equivalent redundant dictionary (ERDCESM) is proposed to enhance the performances of source field reconstruction for different types of sources. Moreover, inspired by the idea of functional beamforming (FB), ERDCESM with order v (ERDCESM- v ) can possess a high dynamic range when detecting the source location. The numerical simulations are carried out at different frequencies to evaluate the performance of the proposed method, and the results suggest that the proposed method performs well both for sparse and even spatially extended sources. The validity and practicality of the proposed method are also verified by the experimental results.

scholarly journals High dynamic range image compression based on visual saliency

2020 ◽  
Vol 9 ◽  
Author(s):  
Jin Wang ◽  
Shenda Li ◽  
Qing Zhu
Keyword(s):  
Image Compression ◽  
Dynamic Range ◽  
Visual Saliency ◽  
High Dynamic Range ◽  
Base Layer ◽  
Range Image ◽  
Coding Region ◽  
Compression Scheme ◽  
High Dynamic ◽  
Hdr Image

Abstract With wider luminance range than conventional low dynamic range (LDR) images, high dynamic range (HDR) images are more consistent with human visual system (HVS). Recently, JPEG committee releases a new HDR image compression standard JPEG XT. It decomposes an input HDR image into base layer and extension layer. The base layer code stream provides JPEG (ISO/IEC 10918) backward compatibility, while the extension layer code stream helps to reconstruct the original HDR image. However, this method does not make full use of HVS, causing waste of bits on imperceptible regions to human eyes. In this paper, a visual saliency-based HDR image compression scheme is proposed. The saliency map of tone mapped HDR image is first extracted, then it is used to guide the encoding of extension layer. The compression quality is adaptive to the saliency of the coding region of the image. Extensive experimental results show that our method outperforms JPEG XT profile A, B, C and other state-of-the-art methods. Moreover, our proposed method offers the JPEG compatibility at the same time.

Estimating Visual Saliency for Omnidirectional HDR Images

2021 ◽  
pp. 249-272
Author(s):  
Kenji Hara
Keyword(s):  
Coordinate System ◽  
Dynamic Range ◽  
Estimation Method ◽  
Visual Saliency ◽  
High Dynamic Range ◽  
Saliency Map ◽  
Overset Grid ◽  
High Dynamic ◽  
Low Dynamic Range ◽  
Hdr Image

A unified decomposition-and-integration-based framework is presented herein for the visual saliency estimation of omnidirectional high dynamic range (HDR) images, which allows straightforward reuse of existing saliency estimation method for typical images with narrow field-of-view and low dynamic range (LDR). First, the proposed method decomposes a given omnidirectional HDR image into multiple partially overlapping LDR images with quasi-uniform spatial resolution and without polar singularities, both spatially and in intensity using a spherical overset grid and a tone-mapping-based synthesis of imaginary multiexposure images. For each decomposed image, a standard saliency estimation method is then applied for typical images. Finally, the saliency map of each decomposed image is optimally integrated from the coordinate system of the overset grid and LDR back to the representation of the coordinate system and HDR of the original image. The proposed method is applied to actual omnidirectional HDR images and its effectiveness is demonstrated.

A HDR Image Compression Algorithm Based on Non-Linear Masking

2010 ◽  
Vol 174 ◽  
pp. 123-126 ◽  
Author(s):  
Ming Zhu ◽  
Zhen Liu ◽  
Dan Dan Yang
Keyword(s):  
Image Compression ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Compression Algorithm ◽  
Good Effect ◽  
Natural Scenes ◽  
Non Linear ◽  
Predictor Model ◽  
Image Compression Algorithm ◽  
Hdr Image

High Dynamic Range Images, with the capability of reproducing the wide lightness range of natural scenes, has been widely used in many areas. But the restrictions of device capability make it necessary to implement tone compression for displaying HDR images. The major research of this paper includes: ① the non-linear masking technology was analyzed and applied to the HDR image tone compression for the first time; ② the specific workflow of the HDR image compression algorithm based on non-linear masking was proposed; ③ VDP (Visible Difference Predictor) model was used to evaluate the performance of the algorithm objectively. The result of algorithm evaluation shows: the non-linear masking can achieve a good effect of tone compression, and greatly reduce the complexity of the algorithm.

scholarly journals Reduced-Dimensional Capture of High-Dynamic Range Images with Compressive Sensing

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Shundao Xie ◽  
Wenfang Wu ◽  
Rongjun Chen ◽  
Hong-Zhou Tan
Keyword(s):  
Compressive Sensing ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Image Sequence ◽  
Range Images ◽  
Multiple Exposure ◽  
Imaging Technology ◽  
Front End ◽  
High Dynamic ◽  
Hdr Image

The range of light illumination in real scenes is very large, and ordinary cameras can only record a small part of this range, which is far lower than the range of human eyes’ perception of light. High-dynamic range (HDR) imaging technology that has appeared in recent years can record a wider range of illumination than the perceptual range of the human eye. However, the current mainstream HDR imaging technology is to capture multiple low-dynamic range (LDR) images of the same scene with different exposures and then merge them into one HDR image, which greatly increases the amount of data captured. The advent of single-pixel cameras (compressive imaging system) has proved the feasibility of obtaining and restoring image data based on compressive sensing. Therefore, this paper proposes a method for reduced-dimensional capture of high dynamic range images with compressive sensing, which includes algorithms for front end (capturing) and back end (processing). At the front end, the K-SVD dictionary is used to compressive sensing the input multiple-exposure image sequence, thereby reducing the amount of data transmitted to the back end. At the back end, the Orthogonal Matching Pursuit (OMP) algorithm is used to reconstruct the input multiple-exposure image sequence. A low-rank PatchMatch algorithm is proposed to merge the reconstructed image sequence to obtain an HDR image. Simulation results show that, under the premise of reducing the complexity of the front-end equipment and the amount of communication data between the front end and the back end, the overall system achieves a good balance between the amount of calculation and the quality of the HDR image obtained.

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