Colorizing gray level images by using wavelet filters
Document Type
Conference Proceeding
Source of Publication
2019 IEEE 10th GCC Conference and Exhibition, GCC 2019
Publication Date
4-1-2019
Abstract
© 2019 IEEE. This paper discusses a new algorithm to produce colored version of gray scale natural still images. This algorithm employs artificial neural network (ANN) to predict RGB channels using the Discrete Wavelet Transform (DWT). A group of natural color images are used to train three ANNs. The trained networks estimate low resolution RGB layers of the gray scale image which are the best match to the trained images. The colored version of the image is produced form the predicted RGB layers and information form grayscale image. The performances of the new algorithm are analyzed subjectively and objectively using the peak signal to noise and Structural Similarity, as well as it is compared to similar algorithm based on discrete cosine transform. Acceptable colorized images were obtained from different still images.
DOI Link
ISBN
9781538694770
Publisher
Institute of Electrical and Electronics Engineers Inc.
Disciplines
Computer Sciences
Keywords
Color images, Colorization, Discrete cosine transform artificial neural network, Discrete wavelet transform, Image processing, Peak signal to noise ratio, Still images
Scopus ID
Recommended Citation
Taher, F.; Darweesh, M.; and Al-Ahmad, H., "Colorizing gray level images by using wavelet filters" (2019). All Works. 969.
https://zuscholars.zu.ac.ae/works/969
Indexed in Scopus
yes
Open Access
no