The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Sintesis imej HDR (Julat Dinamik Tinggi) ialah kaedah yang mengambil gambar pemandangan dengan julat pencahayaan yang luas dan menghasilkan semula imej yang hampir dengan pemandangan visual sebenar pada paparan LDR (Julat Dinamik Rendah). Secara umum, imej HDR dihasilkan semula dengan mengambil imej dengan pelbagai dedahan kamera dan menggunakan sintesis nada beberapa imej. Dalam kertas kerja ini, kami mencadangkan kaedah pemetaan nada imej HDR berdasarkan fungsi kecerahan visual menggunakan imej dwi terdedah dan algoritma sintesis berdasarkan keliling setempat. Algoritma yang dicadangkan telah menambah baik ralat sempadan dan keseimbangan warna berbanding dengan kaedah sedia ada. Selain itu, ia menambah baik kekaburan dan penguatan hingar akibat percampuran imej.
Sung-Hak LEE
Kyungpook National University
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Salinan
Sung-Hak LEE, "HDR Image Synthesis Using Visual Brightness Mapping and Local Surround-Based Image Fusion" in IEICE TRANSACTIONS on Electronics,
vol. E102-C, no. 11, pp. 802-809, November 2019, doi: 10.1587/transele.2019DIP0001.
Abstract: An HDR (High Dynamic Range) image synthesis is a method which is to photograph scenes with wide luminance range and to reproduce images close to real visual scenes on an LDR (Low Dynamic Range) display. In general, HDR images are reproduced by taking images with various camera exposures and using the tone synthesis of several images. In this paper, we propose an HDR image tone mapping method based on a visual brightness function using dual exposed images and a synthesis algorithm based on local surround. The proposed algorithm has improved boundary errors and color balance compared with existing methods. Also, it improves blurring and noise amplification due to image mixing.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/transele.2019DIP0001/_p
Salinan
@ARTICLE{e102-c_11_802,
author={Sung-Hak LEE, },
journal={IEICE TRANSACTIONS on Electronics},
title={HDR Image Synthesis Using Visual Brightness Mapping and Local Surround-Based Image Fusion},
year={2019},
volume={E102-C},
number={11},
pages={802-809},
abstract={An HDR (High Dynamic Range) image synthesis is a method which is to photograph scenes with wide luminance range and to reproduce images close to real visual scenes on an LDR (Low Dynamic Range) display. In general, HDR images are reproduced by taking images with various camera exposures and using the tone synthesis of several images. In this paper, we propose an HDR image tone mapping method based on a visual brightness function using dual exposed images and a synthesis algorithm based on local surround. The proposed algorithm has improved boundary errors and color balance compared with existing methods. Also, it improves blurring and noise amplification due to image mixing.},
keywords={},
doi={10.1587/transele.2019DIP0001},
ISSN={1745-1353},
month={November},}
Salinan
TY - JOUR
TI - HDR Image Synthesis Using Visual Brightness Mapping and Local Surround-Based Image Fusion
T2 - IEICE TRANSACTIONS on Electronics
SP - 802
EP - 809
AU - Sung-Hak LEE
PY - 2019
DO - 10.1587/transele.2019DIP0001
JO - IEICE TRANSACTIONS on Electronics
SN - 1745-1353
VL - E102-C
IS - 11
JA - IEICE TRANSACTIONS on Electronics
Y1 - November 2019
AB - An HDR (High Dynamic Range) image synthesis is a method which is to photograph scenes with wide luminance range and to reproduce images close to real visual scenes on an LDR (Low Dynamic Range) display. In general, HDR images are reproduced by taking images with various camera exposures and using the tone synthesis of several images. In this paper, we propose an HDR image tone mapping method based on a visual brightness function using dual exposed images and a synthesis algorithm based on local surround. The proposed algorithm has improved boundary errors and color balance compared with existing methods. Also, it improves blurring and noise amplification due to image mixing.
ER -