Colorizing Gray Level Images by using Wavelet Filters

F. Taher, M. Darweesh, H. Al-Ahmad
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引用次数: 0

Abstract

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.
用小波滤波器对灰度图像进行着色
本文讨论了一种生成彩色灰度自然静止图像的新算法。该算法采用离散小波变换(DWT),利用人工神经网络(ANN)对RGB信道进行预测。使用一组自然彩色图像来训练三个人工神经网络。训练后的网络估计出与训练图像最匹配的灰度图像的低分辨率RGB层。图像的彩色版本由预测的RGB层产生,信息形成灰度图像。利用峰值信噪比和结构相似度对新算法的主客观性能进行了分析,并与基于离散余弦变换的相似算法进行了比较。从不同的静态图像中获得可接受的彩色图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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