The high dynamic range imaging pipeline

· Linköping Studies in Science and Technology. Dissertations 30 巻 · Linköping University Electronic Press
5.0
3 件のレビュー
電子書籍
132
ページ
評価とレビューは確認済みではありません 詳細

この電子書籍について

Techniques for high dynamic range (HDR) imaging make it possible to capture and store an increased range of luminances and colors as compared to what can be achieved with a conventional camera. This high amount of image information can be used in a wide range of applications, such as HDR displays, image-based lighting, tone-mapping, computer vision, and post-processing operations. HDR imaging has been an important concept in research and development for many years. Within the last couple of years it has also reached the consumer market, e.g. with TV displays that are capable of reproducing an increased dynamic range and peak luminance.

This thesis presents a set of technical contributions within the field of HDR imaging. First, the area of HDR video tone-mapping is thoroughly reviewed, evaluated and developed upon. A subjective comparison experiment of existing methods is performed, followed by the development of novel techniques that overcome many of the problems evidenced by the evaluation. Second, a largescale objective comparison is presented, which evaluates existing techniques that are involved in HDR video distribution. From the results, a first open-source HDR video codec solution, Luma HDRv, is built using the best performing techniques. Third, a machine learning method is proposed for the purpose of reconstructing an HDR image from one single-exposure low dynamic range (LDR) image. The method is trained on a large set of HDR images, using recent advances in deep learning, and the results increase the quality and performance significantly as compared to existing algorithms.

The areas for which contributions are presented can be closely inter-linked in the HDR imaging pipeline. Here, the thesis work helps in promoting efficient and high-quality HDR video distribution and display, as well as robust HDR image reconstruction from a single conventional LDR image.

評価とレビュー

5.0
3 件のレビュー

この電子書籍を評価する

ご感想をお聞かせください。

読書情報

スマートフォンとタブレット
AndroidiPad / iPhone 用の Google Play ブックス アプリをインストールしてください。このアプリがアカウントと自動的に同期するため、どこでもオンラインやオフラインで読むことができます。
ノートパソコンとデスクトップ パソコン
Google Play で購入したオーディブックは、パソコンのウェブブラウザで再生できます。
電子書籍リーダーなどのデバイス
Kobo 電子書籍リーダーなどの E Ink デバイスで読むには、ファイルをダウンロードしてデバイスに転送する必要があります。サポートされている電子書籍リーダーにファイルを転送する方法について詳しくは、ヘルプセンターをご覧ください。