In this work, a novel method for color video compression using key-frame based color transfer has been proposed. In this
scheme, compression is achieved by discarding the color information of all but few selected frames. These selected
frames are either the key frames (frame selected by a key frame selection algorithm) or the Intra coded (I) frames. The
partially colored video is compressed using a standard encoder thereby achieving higher compression. In the proposed
decoder, a standard decoder first generates the partially colored video sequence from the compressed input. A color
transfer algorithm is then used for generating the fully colored video sequence. The complexity of the proposed decoder
is close to a standard decoder, allowing its use in wide variety of applications like video broadcasting, video streaming,
hand-held devices etc.
Proc. SPIE. 7241, Color Imaging XIV: Displaying, Processing, Hardcopy, and Applications
KEYWORDS: Image processing algorithms and systems, Visualization, Image segmentation, Image processing, Video, Video processing, Motion measurement, Motion estimation, 3D image processing, RGB color model
Colorization is a computer-aided process of adding color to a grayscale image or video. The task
of colorizing a grayscale image involves assigning three dimensional (RGB) pixel values to an
image which varies along only one dimension (luminance or intensity). Since different colors may
have the same luminance value but vary in hue or saturation, mapping between intensity and
color is not unique, and colorization is ambiguous in nature, requiring some amount of human
interaction or external information. In this paper we propose a semi-automatic process for
colorization where the user indicates how each region should be colored by putting the desired
color marker in the interior of the region. The algorithm based on the position and color of the
markers, segments the image and colors it. In order to colorize videos, few reference frames are
chosen manually from a set of automatically generated key frames and colorized using the above
marker approach and their chrominance information is then transferred to the other frames in the
video using a color transfer technique making use of motion estimation. The colorization results
obtained are visually very good. In addition the amount of manual intervention is reduced since
the user only has to apply color markers on few selected reference frames and the proposed
algorithm colors the entire video sequence.
In this work, a novel approach for restoration of Color faded images is presented. A Uniform fading model is
assumed. The algorithm comprises of matching the blocks in the image with some predefined reference blocks.
These reference blocks are used to represent the true color of objects. The Correlation Coefficient is used as a
measure for similarity matching. The threshold used for determining the matching is chosen adaptively from the
image itself. A fade detection algorithm is proposed for distinguishing color faded images from the images with
true cast. The algorithm has been tested and validated over a number of image sequences.