scholarly journals Improved Single Haze Removal using Weighted Filter and Gaussian-Laplacian

2020 ◽  
Vol 8 (2) ◽  
pp. 26-31
Author(s):  
Ajeeta Singh Bhadoria ◽  
Vandana Vikas Thakre
Keyword(s):  
Median Filter ◽  
Depth Map ◽  
Vital Role ◽  
Computer Applications ◽  
Color Channel ◽  
High Quality ◽  
Haze Removal ◽  
Imaging Model ◽  
Laplacian Filter ◽  
Bad Weather

Generally computer applications use digital images. Digital image plays a vital role in the analysis and explanation of data, which is in the digital form. Images and videos of outside scenes are generally affected by the bad weather environment such as haze, fog, mist etc. It will result in bad visibility of the scene caused by the lack of quality. This paper exhibits a study about various image defogging techniques to eject the haze from the fog images caught in true world to recuperate a fast and enhanced nature of fog free images. In this paper, we propose a simple but effective the weighted median (WM) filter was first presented as an overview of the standard median filter, where a nonnegative integer weight is assigned to each position in the filter window image .Gaussian and laplacian pyramids are applying Gaussian and laplacian filter in an image in cascade order with different kernel sizes of gaussian and laplacian filter .The dark channel prior is a type of statistics of the haze-free outdoor images. It is based on a key observation - most local patches in haze-free outdoor images contain some pixels which have very low intensities in at least one-color channel. Using this prior with the haze imaging model, we can directly estimate the thickness of the haze and recover a high-quality haze-free image. Results on a variety of outdoor haze images demonstrate the power of the proposed prior. Moreover, a high-quality depth map can also be obtained as a by-product of haze removal and Calculate the PSNR and MSE of three sample images.

scholarly journals Image Dehazing Technique Based On DWT Decomposition and Intensity Retinex Algorithm

2019 ◽  
pp. 116-122
Author(s):  
Sunita Shukla ◽  
Silky Pareyani
Keyword(s):  
Median Filter ◽  
Weather Conditions ◽  
Input Image ◽  
Single Image ◽  
Distance Information ◽  
Haze Removal ◽  
Imaging Model ◽  
Single Input ◽  
Adjacent Pixel ◽  
Different Depths

Conventional designs use multiple image or single image to deal with haze removal. The presented paper uses median filer with modified co-efficient (16 adjacent pixel median) and estimate the transmission map and remove haze from a single input image. The median filter prior(co-efficient) is developed based on the idea that the outdoor visibility of images taken under hazy weather conditions seriously reduced when the distance increases. The thickness of the haze can be estimated effectively and a haze-free image can be recovered by adopting the median filter prior and the new haze imaging model. Our method is stable to image local regions containing objects in different depths. Our experiments showed that the proposed method achieved better results than several state-of-the-art methods, and it can be implemented very quickly. Our method due to its fast speed and the good visual effect is suitable for real-time applications. This work confirms that estimating the transmission map using the distance information instead the color information is a crucial point in image enhancement and especially single image haze removal.

Haze removal with automatic recovery of atmospheric light

2019 ◽  
Vol 34 (01n03) ◽  
pp. 2040064
Author(s):  
Ruxi Xiang ◽  
Xifang Zhu ◽  
Feng Wu
Keyword(s):  
Color Constancy ◽  
Weather Condition ◽  
Input Image ◽  
Statistical Characteristics ◽  
User Input ◽  
Haze Removal ◽  
Salient Region ◽  
Imaging Model ◽  
Bad Weather ◽  
Atmospheric Light

Most haze removal methods are based on the classical haze imaging model, which can effectively describe the image from the haze, where one of the key factors is the atmospheric light. Existing methods either depend on the user input or keep to the color constancy. In this paper, we present a new and effective method for computing the atmospheric light based on the salient region of the input haze image. The method computes the salient map and the darkness channel map of the input image and adaptively selects the region of the atmospheric light according to the assumption that the atmospheric light does not belong to the salient region of the input image. Then, the atmospheric light is estimated by combining the statistical characteristics between the darkness channel and the region of the atmospheric light. Finally, the transmission map is computed and refined by the weight-guided filter and the clear image without the haze is produced. Compared with some existing methods, a number of experimental results show that the proposed method can not only accurately recover the atmospheric light, but also effectively remove the haze from bad weather condition and improve the image quality such as the contrast, sharpness and color.

scholarly journals Improved Color Attenuation Prior for Single-Image Haze Removal

2019 ◽  
Vol 9 (19) ◽  
pp. 4011 ◽  
Author(s):  
Dat Ngo ◽  
Gi-Dong Lee ◽  
Bongsoon Kang
Keyword(s):  
Background Noise ◽  
State Of The Art ◽  
Median Filter ◽  
Depth Map ◽  
Superior Performance ◽  
Single Image ◽  
Vast Number ◽  
Haze Removal ◽  
Quantitative Metrics ◽  
Successful Resolution

This paper proposes a single image haze removal algorithm that shows a marked improvement on the color attenuation prior-based method. Through a vast number of experiments on a wide variety of images, it is discovered that there are problems in the color attenuation prior, such as color distortion and background noise, which arise due to the fact that the priors do not hold true in all circumstances. Successful resolution of these problems using the proposed algorithm shows its superior performance to other state-of-the-art methods in terms of both subjective visual quality and quantitative metrics, on both synthetic and natural hazy image datasets. The proposed algorithm also is computationally friendly, due to the use of an efficient quad-decomposition algorithm for atmospheric light estimation and a simple modified hybrid median filter for depth map refinement.

Fast Single Image Haze Removal Scheme Using Self-Adjusting

2019 ◽  
Vol 3 (1) ◽  
pp. 42-57
Author(s):  
Sangita Roy ◽  
Sheli Sinha Chaudhuri
Keyword(s):  
Optical Model ◽  
Classical Problem ◽  
High Contrast ◽  
Single Image ◽  
High Quality ◽  
Pixel Intensity ◽  
Haze Removal ◽  
Real Time Applications ◽  
Bad Weather ◽  
Minimum Intensity

At present the classical problem of visibility improvement is hot topic of research. An image formation optical model is presented where a clear day image has high contrast with respect to an image plagued with bad weather. A degraded daytime image has high intensity with minimum deviation among pixels in every channel. No reference digital image haze removal is a problem. The static haziness factor for all types of images cannot be applicable for effective haze removal. A minimum intensity channel of the three RGB channels is estimated as transmission of an image with a dynamic haziness factor to be a ratio of minimum to maximum pixel intensity of the hazy image. Adaptive contrast, extinction coefficient, the maximum visible distance of hazy images as well as dehazed images from each image are evaluated uniquely. The resulting high-quality haze free image with linear computational complexity O(n) is appropriate for real time applications. The effectiveness of the technique is validated by quantitative, and qualitative evaluations.

Image Haze Removal Based Dark Channel Prior

2014 ◽  
Vol 536-537 ◽  
pp. 186-191
Author(s):  
Bai Lin Lin
Keyword(s):  
Model Building ◽  
Image Database ◽  
Local Area ◽  
Dark Channel Prior ◽  
Color Channel ◽  
High Quality ◽  
Haze Removal ◽  
Dark Channel ◽  
Statistical Laws ◽  
Interference Image

This paper describes the image based on dark channel prior to fog. Dark colors from the statistical laws of outdoor priori no fog image database, it was such a key observation was based on the fact that - the vast majority of each local area outdoor image without fog are present strength of certain of at least one color channel low value pixels. Using this model building, directly estimate the concentration of fog and mist removal recover high quality interference image. Experiments show that the dark channel prior to remove the image haze becomes simple and effective.

Single image fog and haze removal based on self-adaptive guided image filter and color channel information of sky region

2017 ◽  
Vol 77 (11) ◽  
pp. 13513-13530 ◽  
Author(s):  
Bo Jiang ◽  
Hongqi Meng ◽  
Jian Zhao ◽  
Xiaolei Ma ◽  
Siyu Jiang ◽  
...  
Keyword(s):  
Single Image ◽  
Color Channel ◽  
Image Filter ◽  
Haze Removal ◽  
Guided Image Filter ◽  
Channel Information ◽  
Self Adaptive

scholarly journals Affordable Homeownership: Solutions For Alleviating Mississauga's Affordable Housing Issue

2021 ◽  
Author(s):  
Jennifer Lynn Ormiston
Keyword(s):  
Quality Of Life ◽  
Affordable Housing ◽  
Vital Role ◽  
High Quality ◽  
Local Economies ◽  
Housing Issue ◽  
Market Trends ◽  
Policies And Programs

This research looks at literature, market trends, and policies and programs pertaining to affordable homeownership. The literature suggests that homeownership contributes to local economies and quality of life and is an important part of creating vibrant societies. This research is important as planning plays a vital role in representing those who cannot represent themselves and ensuring that a high quality of life is accessible to everyone. It explores the affordable housing issue in Mississauga and identifies the programs that currently exist to alleviate affordable housing issues. The recommendations are intended to guide Mississauga in the next steps of alleviating affordable homeownership issues. The recommendations provided are transient and can be used as a template for other municipalities in the Greater Golden Horseshoe Area alleviate similar issues.

A High Quality Depth Map Upsampling Method Robust to Misalignment of Depth and Color Boundaries

2013 ◽  
Vol 75 (1) ◽  
pp. 23-37 ◽  
Author(s):  
Jaekwang Kim ◽  
Jaeho Lee ◽  
Seung-Ryong Han ◽  
Dowan Kim ◽  
Jongsul Min ◽  
...  
Keyword(s):  
Depth Map ◽  
High Quality ◽  
Depth Map Upsampling

scholarly journals Robust and brittle secured video for IOT

2018 ◽  
Vol 7 (2.20) ◽  
pp. 93 ◽  
Author(s):  
K Lakshmi Narayanan ◽  
G P. Ramesh ◽  
V Divya
Keyword(s):  
High Performance ◽  
Electronic Device ◽  
Digital Camera ◽  
Vital Role ◽  
Arithmetic Coding ◽  
High Quality ◽  
Binary Arithmetic ◽  
Computer Based ◽  
The Military ◽  
The Internet Of Things

In this paper the system is mainly designed for the  military purpose security since now-a-days securing our military has become a difficult task .our live is mainly dependent on other objects mainly we are computer based living and digital image processing plays a vital role in it. This process has much advantage as well as some disadvantage. A VLSI circuit is built with many millions of IC chip, so it is considered to be indivisible for the construction purpose. The internet-of things (Iot) is a electronic device which is connected to the vehicle and the building item which is used to generate many secured techniques which is connected with the software, electrical, electronics and mechectronics devices and human recourses also. Better Portable Graphics Algorithm with a Context-Adaptive Binary Arithmetic Coding (CABAC) encoding algorithm is used in the existing system this process is affected by the Gaussian noise, low compression ratio and time delay to overcome above issues and  enhanced with Secure Better Portable Graphics (SBPG) compression algorithm with HEVC is present .The proposed architecture is suitable for high performance imaging in the Iot and for the high quality compression files and secured transformation of image and video captured in the digital camera. Encryption and watermarking are the two technique used in the process. The watermarking technique is more secure than the previous system. This process produces high quality JPEG, and high PSNR ratio. The scrambling algorithm is used in the encryption process. It is used for providing secured image.

scholarly journals Detection of a repeated transit signature in the light curve of the enigma star KIC 8462852: A possible 928-day period

2017 ◽  
Vol 608 ◽  
pp. A132 ◽  
Author(s):  
F. Kiefer ◽  
A. Lecavelier des Étangs ◽  
A. Vidal-Madjar ◽  
G. Hébrard ◽  
V. Bourrier ◽  
...  
Keyword(s):  
Light Curve ◽  
Production Rate ◽  
A Priori ◽  
Ring System ◽  
Striking Similarity ◽  
Dust Production ◽  
High Quality ◽  
Bad Weather ◽  
Absorption Features

As revealed by its peculiar Kepler light curve, the enigmatic star KIC 8462852 undergoes short and deep flux dimmings at a priori unrelated epochs. This star presents nonetheless all other characteristics of a quiet 1 Gyr old F3V star. These dimmings resemble the absorption features expected for the transit of dust cometary tails. The exocomet scenario is therefore most commonly advocated. We reanalysed the Kepler data and extracted a new high-quality light curve to allow for the search of shallow signatures of single or a few exocomets. We discovered that among the 22 flux dimming events that we identified, two events present a striking similarity. These events occurred 928.25 days apart and lasted for 4.4 days with a drop in the star brightness by 1000 ppm. We show that the light curve of these events is well explained by the occultation of the star by a giant ring system or by the transit of a string of half a dozen exocomets with a typical dust production rate of 105–106 kg s-1. Assuming that these two similar events are related to the transit of the same object, we derive a period of 928.25 days. The following transit was expected in March 2017 but bad weather prohibited us from detecting it from ground-based spectroscopy. We predict that the next event will occur between 3−8 October 2019.

Sign in / Sign up

Export Citation Format

Share Document