Development Of Digital Image Re-Colouring Algorithm
Re-colouring image or colorization is the process of adding colour to monochrome image or greyscale image which it is typically involve segmentation of images into regions and tracking these regions across image sequence. Colorization have been developed from time to time in order to improve its p...
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| Main Author: | |
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| Format: | Monograph |
| Language: | English |
| Published: |
Universiti Sains Malaysia
2018
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| Online Access: | http://eprints.usm.my/53471/1/Development%20Of%20Digital%20Image%20Re-Colouring%20Algorithm_Noorfairuse%20Mohamad%20Noor_E3_2018.pdf http://eprints.usm.my/53471/ |
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| Summary: | Re-colouring image or colorization is the process of adding colour to monochrome image or greyscale image which it is typically involve segmentation of images into regions and tracking these regions across image sequence. Colorization
have been developed from time to time in order to improve its performance and to make sure that the system developed is user friendly. First colorization method was by determined the pixels region manually and added colour to the region manually. This colorization method spends a lot of cost and time consume. Another method is example-based colorization by transferring colour from a reference colour image. The artistic control of this method is quite indirect because the user is required to find a references image containing the desired colour over region. This thesis will present the simple colorization method which is scribble colorization method that based on a simple
premise which is neighbouring pixels in space time that have similar intensities should have similar colour. The user only needs to annotate the image with a few colour scribbles and the indicated colours are automatically propagated in both space and time to produce a fully colorized image. Qualitative analysis and quantitative analysis are used to verify the result images. The result images are compared based on the quality of the colour and the value of PSNR. High value of PNSR indicated that the result image and the ground truth image are similar. |
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