Development Of Contrast Enhancement Method For Digital Images
Photos captured in the dark environments, which have insufficient or uneven lighting conditions, might lead to low contrast images. The night images are looked dark and not clear as compared to day images. Image enhancement methods can be applied to improve the image quality. Histogram equalization...
| Main Author: | |
|---|---|
| Format: | Monograph |
| Language: | English |
| Published: |
Universiti Sains Malaysia
2017
|
| Subjects: | |
| Online Access: | http://eprints.usm.my/52980/ http://eprints.usm.my/52980/1/Development%20Of%20Contrast%20Enhancement%20Method%20For%20Digital%20Images_Yeoh%20Seng%20Cheng_E3_2017.pdf |
| _version_ | 1848882398541905920 |
|---|---|
| author | Yeoh, Seng Cheng |
| author_facet | Yeoh, Seng Cheng |
| author_sort | Yeoh, Seng Cheng |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Photos captured in the dark environments, which have insufficient or uneven lighting conditions, might lead to low contrast images. The night images are looked dark and not clear as compared to day images. Image enhancement methods can be applied to improve the image quality. Histogram equalization (HE) method is a common image enhancement method. Although researchers had proposed many enhancement methods which including global and local histogram equalization, there are still some problems faced which include over enhancement, shift of mean brightness and loss of details. Hence, two image enhancement methods were developed by cascading exposure sub-image histogram equalization (ESIHE) and contrast limited adaptive histogram equalization (CLAHE) in different sequences. ESIHE is a global histogram equalization based method, while CLAHE is a local histogram equalization based method. Then, these two proposed methods were compared with existing HE based methods qualitatively and quantitatively. The qualitative assessment is visual assessment survey, while quantitative assessments are. noise standard deviation (NSD), image variance (IV), speckle index (SI) and contrast per pixel (CPP). Based on the assessments, the method that applied ESIHE then followed by CLAHE is able to enhance images better than the method applied CLAHE first and followed by ESIHE. The output image have a natural appearance, high contrast, and the details of image are clear. |
| first_indexed | 2025-11-15T18:34:17Z |
| format | Monograph |
| id | usm-52980 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T18:34:17Z |
| publishDate | 2017 |
| publisher | Universiti Sains Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-529802022-06-21T08:27:53Z http://eprints.usm.my/52980/ Development Of Contrast Enhancement Method For Digital Images Yeoh, Seng Cheng T Technology TK Electrical Engineering. Electronics. Nuclear Engineering Photos captured in the dark environments, which have insufficient or uneven lighting conditions, might lead to low contrast images. The night images are looked dark and not clear as compared to day images. Image enhancement methods can be applied to improve the image quality. Histogram equalization (HE) method is a common image enhancement method. Although researchers had proposed many enhancement methods which including global and local histogram equalization, there are still some problems faced which include over enhancement, shift of mean brightness and loss of details. Hence, two image enhancement methods were developed by cascading exposure sub-image histogram equalization (ESIHE) and contrast limited adaptive histogram equalization (CLAHE) in different sequences. ESIHE is a global histogram equalization based method, while CLAHE is a local histogram equalization based method. Then, these two proposed methods were compared with existing HE based methods qualitatively and quantitatively. The qualitative assessment is visual assessment survey, while quantitative assessments are. noise standard deviation (NSD), image variance (IV), speckle index (SI) and contrast per pixel (CPP). Based on the assessments, the method that applied ESIHE then followed by CLAHE is able to enhance images better than the method applied CLAHE first and followed by ESIHE. The output image have a natural appearance, high contrast, and the details of image are clear. Universiti Sains Malaysia 2017-06-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/52980/1/Development%20Of%20Contrast%20Enhancement%20Method%20For%20Digital%20Images_Yeoh%20Seng%20Cheng_E3_2017.pdf Yeoh, Seng Cheng (2017) Development Of Contrast Enhancement Method For Digital Images. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Elektrik & Elektronik. (Submitted) |
| spellingShingle | T Technology TK Electrical Engineering. Electronics. Nuclear Engineering Yeoh, Seng Cheng Development Of Contrast Enhancement Method For Digital Images |
| title | Development Of Contrast Enhancement Method For Digital Images |
| title_full | Development Of Contrast Enhancement Method For Digital Images |
| title_fullStr | Development Of Contrast Enhancement Method For Digital Images |
| title_full_unstemmed | Development Of Contrast Enhancement Method For Digital Images |
| title_short | Development Of Contrast Enhancement Method For Digital Images |
| title_sort | development of contrast enhancement method for digital images |
| topic | T Technology TK Electrical Engineering. Electronics. Nuclear Engineering |
| url | http://eprints.usm.my/52980/ http://eprints.usm.my/52980/1/Development%20Of%20Contrast%20Enhancement%20Method%20For%20Digital%20Images_Yeoh%20Seng%20Cheng_E3_2017.pdf |