An Interactive Framework for Video Colorization

Teng, Shenghua; Shen, Yiping; Zhao, Zhihua; Li, Lei; Cao, Maoyong

doi:10.1109/icig.2013.24

Cited by 2 publications

(4 citation statements)

References 8 publications

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“…Drawing on the fundamental work described in [39], Wang [40] adopts differential methods to improve the boundary blur dilemma and achieves a certain degree of enhancement in the process. Wang's method attempts to refine the processing of edges within images through careful application of differential operators, striving to strike a balance between edge preservation and attenuation of blurring phenomena.…”

Section: Colorization Of Grayscale Imagesmentioning

confidence: 99%

“…In this paper, we focus on integrating the p-Laplacian method with manual intervention using penalty functions and a comprehensive application of the methods elaborated in [29,39,40], supervised by advanced machine learning models. This fusion provides theoretical support for semi-automatic colorization of monochromatic visual representations.…”

Section: Colorization Of Grayscale Imagesmentioning

confidence: 99%

“…In 2006, Teng proposed a novel grayscale image colorization paradigm, described in [39]. The user initializes the process by inscribing color boundaries on the image, which are then used as guides for color diffusion facilitated by the p-Laplacian.…”

Section: Colorization Of Grayscale Imagesmentioning

confidence: 99%

“…However, R, G, andB still need to be solved. At the same time, the YCbCr method adopted in articles [39], [40] is just a different set of color descriptions. The conversion formula is:…”

Section: 23 Encryption and Transmission Of Diagonalized The Square Ma...mentioning

confidence: 99%

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A Feasible Solution for Image Encryption, Restoration, and Colorization Based on the Methods of Weighted Conjugate Gradient, RSA Encryption, and Deep Learning.

Yuan,

Zhang

2024

Preprint

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In contemporary society, people are increasingly aware of environmental issues. Coinciding with this development is the arrival of the era of big data, accompanied by significant advances in artificial intelligence. These technologies are increasingly used to collect, systematize and review data to facilitate informed decision-making processes. Ecological image processing stands out as a critical application in this technological field. In the rapid development of deep learning methods, challenges still exist due to the impact of training models on machine performance. In some cases, machine performance is still not ideal. This paper introduces a novel weighted conjugate gradient (WCG) algorithm based on the classic conjugate gradient method, which has better performance in image restoration tasks. Meanwhile, this paper extends the RSA encryption method to the encrypted transmission of the matrix framework to ensure data security during the transmission process. In addition, under the supervision of established machine learning vision models, this paper adopts a penalty function strategy combined with the p-Laplacian operator and manual methods to provide users with enhanced control over manual intervention in grayscale image colorization, thereby enriching Visual fidelity and interpretability of images. The numerical calculation method adopts the WCG algorithm innovatively proposed in this article. Based on the above, the framework proposed in this paper describes a quasi-automatic method for image encryption, transmission, recovery, and colorization. This framework not only ensures that users can intervene and adjust but also maximizes machine execution speed. The framework bridges the gap between fully automated systems and fully manual operating systems, trying to find a balance between convenience and accuracy. At the same time, the Matrix RSA encryption method ensures security during transmission. This framework has significant advantages in applications in professional fields that have specific requirements for accuracy, convenience, and security.

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Section: Colorization Of Grayscale Imagesmentioning

confidence: 99%

Section: Colorization Of Grayscale Imagesmentioning

confidence: 99%

Section: Colorization Of Grayscale Imagesmentioning

confidence: 99%

“…However, R, G, andB still need to be solved. At the same time, the YCbCr method adopted in articles [39], [40] is just a different set of color descriptions. The conversion formula is:…”

Section: 23 Encryption and Transmission Of Diagonalized The Square Ma...mentioning

confidence: 99%

See 2 more Smart Citations