In colorization-based coding the encoder picks a couple of representative pixels (RP) for which the chrominance values and the positions are sent to the decoder, although in the decoder, the chrominance values for all the pixels are recreated by colorization techniques. The fundamental issue in colorization-based coding is the manner by which to obtain the RP well in this manner the compression...

We develop a fully automatic image colorization system. Our approach leverages recent advances in deep networks, exploiting both low-level and semantic representations. As many scene elements naturally appear according to multimodal color distributions, we train our model to predict per-pixel color histograms. This intermediate output can be used to automatically generate a color image, or furt...

The paper presents an innovative technique for colorization of grayscale images. Here the colors from some source color image are picked up and sprayed into the to be colored grayscale image. The color palette used in colorization technique discussed here is generated using the Linde Buzo and Gray (LBG) codebook. The technique is tested using various VQ codebook sizes like 32, 64, 128, 256 and ...

In this paper, the colorization-based coding problem has been solved using smooth L0 (SL0) and L1 norm (OMP) minimization sparse recovery algorithms. In colorization-based coding method at the encoder, only few representative pixels (RP) for the chrominance values are sent along with luminance part of image to the decoder where the chrominance values for all the pixels are reconstructed by colo...

Recent research suggests that colorization models have the capability of generating plausible color versions from grayscale images. In this paper, we investigate whether colorization prior to gender classification improves classification performance on the FERET grayscale face dataset. For this, we colorize the images using an existing Lab colorization model, both with and without class rebalan...

Recent research suggests that colorization models have the capability of generating plausible color versions from grayscale images. In this paper, we investigate whether colorization prior to gender classification improves classification performance on the FERET grayscale face dataset. For this, we colorize the images using an existing Lab colorization model, both with and without class rebalan...

Image colorization adds color to grayscale images. It not only increases the visual appeal of grayscale images, but also enriches the information contained in scientific images that lack color information. Most existing methods of colorization require laborious user interaction for scribbles or image segmentation. To eliminate the need for human labor, we develop an automatic image colorization...

In this work we focus on the problem of colorization for image compression. Since color information occupies a large proportion of the total storage size of an image, a method that can predict accurate color from its grayscale version can produce a dramatic reduction in image file size. But colorization for compression poses several challenges. First, while colorization for artistic purposes si...

Colorization is a computer-assisted process of adding color to a monochrome image or movie. Most current colorization algorithms either require a significant user effort or have large computational time. In any case, colorization of real size images remains a time-consuming, tedious task. In this paper we present a new colorization method, based on GrowCut image segmentation algorithm. In our a...

Realistic colorization of videos has been of great interest to the artistic community, primarily for restoring historical color films and colorizing legacy videos. In this project, we experimented with several methods in order to automatically colorize videos on a frame-by-frame basis. We focused on rectifying two primary issues encountered with video colorizations : lack of color consistency b...