Colorizing with Examples and Deep Learning
/via http://bruxy.regnet.cz/web/gfx/EN/colorize/ Colorization — adding colors to gray-scale images — is deceptively tricky. The underlying issue is that the resultant image needs to be perceptually meaningful, and visually appealing. Which is all well and good, but, well, meaningful and visually appealing to whom ? In the image above, • Is the fence painted? Or, if not, what shades of brown should the fence be? • That grass— should it be green, blue-green, straw yellow, or brown? • And the trees? And the leaves? You get it — the point here being that there really is no uniquely correct solution, and so much of what happens is about the intent of the person doing the colorizing Historically, this was all deeply manual, with the work consisting of literally painting the image. Software did help, but there was still a lot of manual work involve — for example, humans would draw a boundary and tell the computer to fill in that boundary with a given color with shading, fad...