| Autor: |
Pavan Kumar, M. P., Poornima, B., Nagendraswamy, H. S., Manjunath, C., Rangaswamy, B. E. |
| Zdroj: |
Multidimensional Systems & Signal Processing; Jun2022, Vol. 33 Issue 2, p401-458, 58p |
| Abstrakt: |
Due to the evolution of computer vision and non-photorealistic rendering (NPR) techniques, enhancements of image features from blatant range images are possible. Conveying the shape from blatant range images are a crucial part of surveillance systems, content-aware analysis, image abstraction and line drawing. In view of this, the work presents a combinational high dynamic range (HDR) and image abstraction framework that can deliver the most effective dirt-free line drawing output to convey the shapes from blatant range images. The proposed framework manipulates the visual features from under/overexposed 2D blatant range images by retaining the prominent tonal information, dominant structural features and suppressing the superfluous details. Significant image properties and quality assessment metrics are effectively enhanced based on the statistical parameters computed and by empirically defined conditions at every stage of the framework. The framework exploits image and objective spatial data to create the dirt-free line drawing in order to recognize amplified elements of the enhanced structure by making use of the Harris key-feature detector algorithm. A sequence of HDR tone mapping operators and NPR image filters are comprehensively integrated through rigorous experimental analysis. Hence, this work empirically retains the prominent tonal and structural features in the frontal region and diminishes the background features in given input images. The work is implemented in MatLab-2020 with a 6.6 teraflops/s high-performance super computation ambience and Tesla P100 graphical processing unit. Efficacy of the presented framework has been validated by executing extensive experimentation on the benchmark datasets such as Ruixing Wang dataset, Flickr repository images and many other interesting datasets are collected. The obtained results are compared with other comparable existing work cited in the literary-works. Furthermore, human visualization perceptual analysis opinion process is also used to evaluate the proposed framework. Significant image abstraction and dirt free line drawing detentions, design challenges, applications and potential work in the domain of non-photorealistic rendering are also envisaged in this paper. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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