An Integrated Filter Based Approach for Image Abstraction and Stylization

Lecture Notes in Electrical Engineering - Multimedia Processing, Communication and Computing Applications ◽

10.1007/978-81-322-1143-3_20 ◽

2013 ◽

pp. 241-252 ◽

Cited By ~ 1

Author(s):

H. S. Nagendra Swamy ◽

M. P. Pavan Kumar

Keyword(s):

Image Abstraction

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Structure-preserving NPR framework for image abstraction and stylization

The Journal of Supercomputing ◽

10.1007/s11227-020-03547-w ◽

2021 ◽

Author(s):

M. P. Pavan Kumar ◽

B. Poornima ◽

H. S. Nagendraswamy ◽

C. Manjunath

Keyword(s):

Structure Preserving ◽

Image Abstraction

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Structure Preserving Non-Photorealistic Rendering Framework for Image Abstraction and Stylization of Low-Illuminated and Underexposed Images

International Journal of Computer Vision and Image Processing ◽

10.4018/ijcvip.2021040102 ◽

2021 ◽

Vol 11 (2) ◽

pp. 22-45

Author(s):

Pavan Kumar ◽

Poornima B. ◽

Nagendraswamy H. S. ◽

Manjunath C.

Keyword(s):

Structural Features ◽

Image Features ◽

Visual Features ◽

Structure Preserving ◽

Photorealistic Rendering ◽

Assessment Techniques ◽

Contemporary Work ◽

Image Abstraction ◽

Future Work ◽

Background Content

The proposed abstraction framework manipulates the visual-features from low-illuminated and underexposed images while retaining the prominent structural, medium scale details, tonal information, and suppresses the superfluous details like noise, complexity, and irregular gradient. The significant image features are refined at every stage of the work by comprehensively integrating a series of AnshuTMO and NPR filters through rigorous experiments. The work effectively preserves the structural features in the foreground of an image and diminishes the background content of an image. Effectiveness of the work has been validated by conducting experiments on the standard datasets such as Mould, Wang, and many other interesting datasets and the obtained results are compared with similar contemporary work cited in the literature. In addition, user visual feedback and the quality assessment techniques were used to evaluate the work. Image abstraction and stylization applications, constraints, challenges, and future work in the fields of NPR domain are also envisaged in this paper.

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