Scholarlink

Colorization of images serves as a transformative tool, imbuing black and white pictures with vitality that mirrors the essence of the captured moment. Beyond merely transitioning aged images into modern color renditions, this process extends its reach to inferring colors for images where conventional color-capturing methods fail. In this paper, we introduce a novel algorithm designed to seamlessly convert grayscale images into perceptually consistent color compositions. We have also developed a novel layer by combining convolutional and lambda layers towards image colorization. Our proposed algorithm represents a significant advancement in the field of image colorization, offering a multifaceted solution to enhance visual storytelling and comprehension.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

\(\lambda \) -Color: Amplifying Long-Range Dependencies for Image Colorization

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Subhankar Ghosh,
  • Saumik Bhattacharya,
  • Prasun Roy,
  • Umapada Pal,
  • Michael Blumenstein

摘要

Colorization of images serves as a transformative tool, imbuing black and white pictures with vitality that mirrors the essence of the captured moment. Beyond merely transitioning aged images into modern color renditions, this process extends its reach to inferring colors for images where conventional color-capturing methods fail. In this paper, we introduce a novel algorithm designed to seamlessly convert grayscale images into perceptually consistent color compositions. We have also developed a novel layer by combining convolutional and lambda layers towards image colorization. Our proposed algorithm represents a significant advancement in the field of image colorization, offering a multifaceted solution to enhance visual storytelling and comprehension.