scholarly journals Sparse Representation Based Inverse Halftoning with Boosted Dictionary1

2021 ◽  
Author(s):  
Jun Yang ◽  
Zihao Liu ◽  
Li Chen ◽  
Ying Wu ◽  
Chen Cui ◽  
...  
Keyword(s):  
Sparse Representation ◽  
Noise Level ◽  
Error Diffusion ◽  
Transform Domain ◽  
Display Devices ◽  
Diffusion Operator ◽  
Halftone Image ◽  
Image Blurring ◽  
Inverse Halftoning

Abstract Halftoning image is widely used in printing and scanning equipment, which is of great significance for the preservation and processing of these images. However, because of the different resolution of the display devices, the processing and display of halftone image are confronted with great challenges, such as Moore pattern and image blurring. Therefore, the inverse halftone technique is required to remove the halftoning screen. In this paper, we propose a sparse representation based inverse halftone algorithm via learning the clean dictionary, which is realized by two steps: deconvolution and sparse optimization in the transform domain to remove the noise. The main contributions of this paper include three aspects: first, we analysis the denoising effects for different training sets and the redundancy of dictionary; Then we propose the improved a sparse representation based denoising algorithm through adaptively learning the dictionary, which iteratively remove the noise of the training set and upgrade the quality of the dictionary; Then the error diffusion halftone image inverse halftoning algorithm is proposed. Finally, we verify that the noise level in the error diffusion linear model is fixed, and the noise level is only related to the diffusion operator. Experimental results show that the proposed algorithm has better PSNR and visual performance than state-of-the-art methods.

scholarly journals Joint Image Deblurring and Matching with Blurred Invariant-Based Sparse Representation Prior

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yuanjie Shao ◽  
Nong Sang ◽  
Juncai Peng ◽  
Changxin Gao
Keyword(s):  
Sparse Representation ◽  
Image Matching ◽  
Image Deblurring ◽  
Image Feature ◽  
Zernike Moment ◽  
Invariant Space ◽  
Pseudo Zernike Moment ◽  
Image Blurring ◽  
Blurred Image

Image matching is important for vision-based navigation. However, most image matching approaches do not consider the degradation of the real world, such as image blur; thus, the performance of image matching often decreases greatly. Recent methods try to deal with this problem by utilizing a two-stage framework—first resorting to image deblurring and then performing image matching, which is effective but depends heavily on the quality of image deblurring. An emerging way to resolve this dilemma is to perform image deblurring and matching jointly, which utilize sparse representation prior to explore the correlation between deblurring and matching. However, these approaches obtain the sparse representation prior in the original pixel space, which do not adequately consider the influence of image blurring and thus may lead to an inaccurate estimation of sparse representation prior. Fortunately, we can extract the pseudo-Zernike moment with blurred invariant from images and obtain a reliable sparse representation prior in the blurred invariant space. Motivated by the observation, we propose a joint image deblurring and matching method with blurred invariant-based sparse representation prior (JDM-BISR), which obtains the sparse representation prior in the robust blurred invariant space rather than the original pixel space and thus can effectively improve the quality of image deblurring and the accuracy of image matching. Moreover, since the dimension of the pseudo-Zernike moment is much lower than the original image feature, our model can also increase the computational efficiency. Extensive experimental results demonstrate that the proposed method performs favorably against the state-of-the-art blurred image matching approach.

Data Hiding Based on Noise-Balanced Error Diffusion in Color Image

2012 ◽  
Vol 182-183 ◽  
pp. 1900-1903
Author(s):  
Hai Sheng Chen ◽  
Bao Lin Tang ◽  
Guang Xue Chen ◽  
Shuang Shuang Wen
Keyword(s):  
Data Hiding ◽  
Color Image ◽  
Color Space ◽  
Error Diffusion ◽  
Hidden Information ◽  
Diffusion Operator ◽  
Halftone Image ◽  
Rgb Color Space ◽  
Hidden Data ◽  
Halftone Images

In the publishing and printing applications, hidden data is embedded into images for copyright protection and ownership generally. In this paper, a reasonable data hiding method based on noise-balanced error diffusion (NBEDF) is proposed, which is applied in color halftone image. Color image is firstly separated into grayscale images from RGB color space to CMYK color space. Secondly, Floyd-Steinberg error diffusion operator is used, and halftone images will be obtained. Finally,through NBEDF, hidden data is embedded in the halftone image which contains the largest amount of information. The experimental results show that hidden information can be visible , when the corresponding decoded image overlays the color image with hidden information. The data hiding method proposed in this paper can be well applied on security printing.

Anti-Print and Scan Halftone Watermarking Algorithm Based on Edge Detection

2013 ◽  
Vol 416-417 ◽  
pp. 1210-1213
Author(s):  
Hua Wen Ai ◽  
Ping Feng Liu ◽  
Sheng Cong Dong
Keyword(s):  
Edge Detection ◽  
Image Watermarking ◽  
Error Diffusion ◽  
Grayscale Image ◽  
Good Resistance ◽  
Visibility Function ◽  
Gray Image ◽  
Halftone Image ◽  
Watermark Embedding ◽  
Edge Points

In order to resist print and scan attacks, a kind of digital halftone image watermarking algorithm is proposed, which is based on the edge detection and improved error diffusion. The edge of gray image is gotten using canny detection. Calculate the noise visibility function values of the edge points. Then, sort the values in ascending order and select the size that equal to the length of watermark as the location of watermark embedding. While the grayscale image turns to halftone image using the improved error diffusion algorithm, binary watermark is embedded in the edge position. Watermark is pretreated with Arnold before embedding to improve the safety of watermark. Experiment results show that the algorithm is good resistance to print and scan attacks, while resistance to shearing, noise and jpeg compression attacks.

Effects of Railway Noise on Residents’ in A Residential Area

2021 ◽  
Vol 3 (01) ◽  
pp. 17-28
Author(s):  
Ria Anggreani Syahputri ◽  
Budi Damianto
Keyword(s):  
Noise Level ◽  
Sleep Disturbances ◽  
Sampling Technique ◽  
Residential Area ◽  
Comfort Level ◽  
Simple Method ◽  
Urban Village ◽  
Noise Measurements ◽  
Influence Of Noise

Population growth in Depok City is large and not in accordance with development land causes many residents’ to build houses with conditions <5 meters from the line of Electric Rail Train or Kereta Rel Listrik (KRL); this causes changes in the quality of the environment, including noise. The objective of this study is to determine the noise level, and the results will be compared with the standard noise level of the residential area; also, to find the influence of noise on residents’. This research was conducted in the area of ​​Rawa Geni Raya Street, 1st Neighborhood, Ratu Jaya Urban Village, Depok City. Noise measurements were carried out at 5-points using a simple method with a noise level measuring instrument (SLM). At one time, the measurement was taken for 10 minutes with a reading time of every 5 seconds. The questionnaire was measured using a Purposive Random Sampling technique, and the number of samples was calculated using the Slovin formula. The results of this study indicate that the 5-point noise level exceeds the recommended threshold according to KEPMEN LH 48 of 1996 and PERMENKES 718/1987 at  55 dB(A). The largest value for the 24-hour noise level (LSM) is at point 1, which is 5 m from the KRL line. The noise level on the weekday is 75.32 dB(A) and 74.24 dB(A) on weekends. According to PERMENKES No 718/1987, the location of point 1 should be included in Area D as an industrial zone, plant, railway station, and bus terminal. The results of questionnaires by 34 respondents showed that the noise generated by KRL was noisy and the majority of respondents agreed the noise affected the comfort level; in terms of health, respondents agreed KRL noise caused sleep disturbances and hearing loss.

scholarly journals Image Denoising Using Discrete Wavelet Transform : A Theoretical Framework

2018 ◽  
Vol 7 (2.16) ◽  
pp. 120
Author(s):  
Praveen Bhargava ◽  
Shruti Choubey ◽  
Rakesh Kumar Bhujade ◽  
Nilesh Jain
Keyword(s):  
Image Denoising ◽  
Ultra Sound ◽  
Discrete Wavelet ◽  
Transform Domain ◽  
Hybrid Filter ◽  
Edge Sharpness ◽  
In Series ◽  
Salt And Pepper ◽  
Image Type

Noise is a random variation in brightness and color in image or simply we can say that unwanted signals are called noise. The noise is mixed with original signal and cause may troubles. Due to the presence of noise, quality of image is reduced and other features like edge sharpness and pattern recognition are badly affected. In image denoising methods to improve the results a hybrid filter is used for better visualization. The hybrid filter is composed with the combination of three filters connected in series. The hybridization has performed much better in case of salt and pepper type of noise and for most of the medical image type, either MRI, CT, SPECT, Ultra Sound. PSNR values show major improvement in comparison of other existing methods. Future, the results obtained from the presented denoising experiments would be tried to be improved further by using this method with other transform domain methods. Finally, the results are concluded that the proposed approach in terms of PSNR, MSE improvement is outperformed. 

Estimation of Signal-Dependent Noise Level Function in Transform Domain via a Sparse Recovery Model

2015 ◽  
Vol 24 (5) ◽  
pp. 1561-1572 ◽  
Author(s):  
Jingyu Yang ◽  
Ziqiao Gan ◽  
Zhaoyang Wu ◽  
Chunping Hou
Keyword(s):  
Noise Level ◽  
Sparse Recovery ◽  
Transform Domain ◽  
Recovery Model ◽  
Level Function

scholarly journals Transform-domain sparse representation based classification for machinery vibration signals

2018 ◽  
Vol 20 (2) ◽  
pp. 979-987 ◽  
Author(s):  
Yu Fajun ◽  
Fan Fuling ◽  
Wang Shuanghong ◽  
Zhou Fengxing
Keyword(s):  
Sparse Representation ◽  
Transform Domain ◽  
Vibration Signals

scholarly journals A Comparative Study between Pre-construction and Construction Phases of Champhai-Zokhawthar Road Construction, Mizoram: Air Quality and Noise Quality Assessments

2019 ◽  
Vol 7 (1) ◽  
pp. 47-53
Author(s):  
Lalven tluanga ◽  
◽  
H. Lalramnghinglova
Keyword(s):  
Economic Growth ◽  
Particulate Matter ◽  
Air Quality ◽  
Comparative Study ◽  
Noise Level ◽  
Road Construction ◽  
Suspended Particulate ◽  
The Mean ◽  
Negative Impacts

In recent years, Mizoram has made immense progress in various sectors and initiated developmental programmes for its economic growth. An important contributing factor to this development and growth is the transport connectivity projects. Although connectivity projects can boost economic growth, its negative effects cannot be neglected. In view of this, the present research studies the impacts of Champhai – Zokhawthar road construction on the air quality and noise quality of the region. This comparative study of the impact on the quality of air and noise pollution in the pre-construction phase and construction phase provide a clear-cut example of the negative impacts caused by road construction and provide a fresh outlook for formulation of improved management plans. Air quality assessment was carried out using High Volume Air Sampler and the following parameters were monitored – suspended particulate matter (SPM), respirable suspended particulate matter (RSPM), nitrogen dioxide (NO2) and sulphur dioxide (SO2). The results indicate that mean SPM concentration was increased by 22.82 µg/m3; RSPM concentration by 14.67 µg/m3; NO2 concentration by 4.08 µg/m3; and SO2 concentration was increased by 0.06 µg/m3 from the pre-construction phase to construction phase. Noise quality assessment was carried out at three sites – Zotlang, Melbuk and Zokhawthar by using Lutron SL-4001 Sound Level Meter and Leq, Lmax and Lmin were recorded and calculated. The mean noise level at Zotlang wasincreased by 8.72 dB (A) and at Melbuk the mean noise level was increased by 9.35 dB (A). However, at Zokhawthar, there was a decrease in mean noise level by 0.13 dB (A). From the present study, it is evident that road construction poses a threat to the air quality and noise quality of the study area and improved measuresneed to betaken to curb its negative impacts

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