{"title":"基于层分解的局部音调映射算子","authors":"Z. Chaithanya, G. Sreenivasulu","doi":"10.58482/ijeresm.v1i1.4","DOIUrl":null,"url":null,"abstract":"Dynamic range of an image directly defines the number of levels it can accommodate in an image. In general, a dynamic range of 256 is in use. Defining dynamic range of an image need to be done by considering the display unit on which the image will be displayed on. If the dynamic range extends over 256, the dynamic range is said to be high dynamic range. This range may extend up to 10,000. This kind of images can’t be displayed on display units which can’t differentiate that many pictorial information. This kind of pictorial information need to be converted so that the regular display units can adapt the format. This must be done without losing much information. This process is very crucial and is done by several tone mapping operators. Tone mapping operators are of two types, global and local. Global tone mapping operators apply same mapping function throughout the image while the local tone mapping operators use different mapping functions for local regions of the image. Though the quality of global TMOs is better, there are many halo effects in the converted image. In this paper, a global TMO based on decomposition is proposed intended to reduce these effects. Image is decomposed in to two layers, base, and detail. A hybrid decomposition and optimization are proposed to improve the quality of converted image.","PeriodicalId":351005,"journal":{"name":"International Journal of Emerging Research in Engineering, Science, and Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Layer Decomposition based Local Tone Mapping Operator\",\"authors\":\"Z. Chaithanya, G. Sreenivasulu\",\"doi\":\"10.58482/ijeresm.v1i1.4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dynamic range of an image directly defines the number of levels it can accommodate in an image. In general, a dynamic range of 256 is in use. Defining dynamic range of an image need to be done by considering the display unit on which the image will be displayed on. If the dynamic range extends over 256, the dynamic range is said to be high dynamic range. This range may extend up to 10,000. This kind of images can’t be displayed on display units which can’t differentiate that many pictorial information. This kind of pictorial information need to be converted so that the regular display units can adapt the format. This must be done without losing much information. This process is very crucial and is done by several tone mapping operators. Tone mapping operators are of two types, global and local. Global tone mapping operators apply same mapping function throughout the image while the local tone mapping operators use different mapping functions for local regions of the image. Though the quality of global TMOs is better, there are many halo effects in the converted image. In this paper, a global TMO based on decomposition is proposed intended to reduce these effects. Image is decomposed in to two layers, base, and detail. A hybrid decomposition and optimization are proposed to improve the quality of converted image.\",\"PeriodicalId\":351005,\"journal\":{\"name\":\"International Journal of Emerging Research in Engineering, Science, and Management\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Emerging Research in Engineering, Science, and Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.58482/ijeresm.v1i1.4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Emerging Research in Engineering, Science, and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.58482/ijeresm.v1i1.4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Layer Decomposition based Local Tone Mapping Operator
Dynamic range of an image directly defines the number of levels it can accommodate in an image. In general, a dynamic range of 256 is in use. Defining dynamic range of an image need to be done by considering the display unit on which the image will be displayed on. If the dynamic range extends over 256, the dynamic range is said to be high dynamic range. This range may extend up to 10,000. This kind of images can’t be displayed on display units which can’t differentiate that many pictorial information. This kind of pictorial information need to be converted so that the regular display units can adapt the format. This must be done without losing much information. This process is very crucial and is done by several tone mapping operators. Tone mapping operators are of two types, global and local. Global tone mapping operators apply same mapping function throughout the image while the local tone mapping operators use different mapping functions for local regions of the image. Though the quality of global TMOs is better, there are many halo effects in the converted image. In this paper, a global TMO based on decomposition is proposed intended to reduce these effects. Image is decomposed in to two layers, base, and detail. A hybrid decomposition and optimization are proposed to improve the quality of converted image.