Zobrazeno 1 - 10
of 157
pro vyhledávání: '"Bongsoon Kang"'
Publikováno v:
Remote Sensing, Vol 16, Iss 19, p 3641 (2024)
Single-image dehazing is an ill-posed problem that has attracted a myriad of research efforts. However, virtually all methods proposed thus far assume that input images are already affected by haze. Little effort has been spent on autonomous single-i
Externí odkaz:
https://doaj.org/article/19586a766a4a4942b8a13258ce2f79f5
Publikováno v:
Symmetry, Vol 16, Iss 9, p 1138 (2024)
Multiplication, division, and square root operations introduce significant challenges in digital signal processing (DSP) systems, traditionally requiring multiple operations that increase execution time and hardware complexity. This study presents a
Externí odkaz:
https://doaj.org/article/53b073de5fa94ffd9d5bf7612e15d7ad
Autor:
Dat Ngo, Bongsoon Kang
Publikováno v:
Symmetry, Vol 16, Iss 6, p 653 (2024)
The acquisition of digital images is susceptible to haze, and images captured under such adverse conditions may impact high-level applications designed for clean input data. Image dehazing emerges as a practical solution to this problem, as it can be
Externí odkaz:
https://doaj.org/article/79e67349098040a5b363c3711d6936fa
Publikováno v:
IEEE Access, Vol 10, Pp 102462-102474 (2022)
Image dehazing is a fundamental problem in computer vision and has hitherto engendered prodigious amounts of studies. Recently, with the well-recognized success of deep learning techniques, this field has been dominated by deep dehazing models. Howev
Externí odkaz:
https://doaj.org/article/aa1d097754d24ef7b155172cf5884211
Publikováno v:
Remote Sensing, Vol 14, Iss 8, p 1852 (2022)
Image dehazing, as a common solution to weather-related degradation, holds great promise for photography, computer vision, and remote sensing applications. Diverse approaches have been proposed throughout decades of development, and deep-learning-bas
Externí odkaz:
https://doaj.org/article/6126572981794f7994b4c73d0b4f82f3
Publikováno v:
Sensors, Vol 22, Iss 5, p 1957 (2022)
Haze is the most frequently encountered weather condition on the road, and it accounts for a considerable number of car crashes occurring every year. Accordingly, image dehazing has garnered strong interest in recent decades. However, although variou
Externí odkaz:
https://doaj.org/article/a0383d6b01bb441a9a21e3b9884875a9
Publikováno v:
Sensors, Vol 21, Iss 19, p 6373 (2021)
Existing image dehazing algorithms typically rely on a two-stage procedure. The medium transmittance and lightness are estimated in the first stage, and the scene radiance is recovered in the second by applying the simplified Koschmieder model. Howev
Externí odkaz:
https://doaj.org/article/9c9029da2eb14eb7af2c9dc390a823ed
Publikováno v:
Sensors, Vol 21, Iss 11, p 3896 (2021)
Haze is a term that is widely used in image processing to refer to natural and human-activity-emitted aerosols. It causes light scattering and absorption, which reduce the visibility of captured images. This reduction hinders the proper operation of
Externí odkaz:
https://doaj.org/article/be2a76ac28df49849d81355d02c36edb
Publikováno v:
Sensors, Vol 21, Iss 8, p 2625 (2021)
Image acquisition is a complex process that is affected by a wide variety of internal and environmental factors. Hence, visibility restoration is crucial for many high-level applications in photography and computer vision. This paper provides a syste
Externí odkaz:
https://doaj.org/article/6afdda3c6194400298861bad4c08826c
Publikováno v:
Sensors, Vol 20, Iss 20, p 5795 (2020)
In recent years, machine vision algorithms have played an influential role as core technologies in several practical applications, such as surveillance, autonomous driving, and object recognition/localization. However, as almost all such algorithms a
Externí odkaz:
https://doaj.org/article/5375a47065ff4152a5c0e7a953b0c4e4