{"title":"基于直方图均衡化和视觉显著性的图像水印框架","authors":"Bishwabara Panda, Manas Ranjan Nayak, Pradeep Kumar Mallick, Abhishek Basu","doi":"10.37936/ecti-cit.2023174.252375","DOIUrl":null,"url":null,"abstract":"This paper proposes a digital image watermarking strategy using histogram equalization and visual Saliency followed by LSB (Least Significant Bit) replacement for better imperceptibility with hiding capacity. With this technique, a saliency map determines lesser-observable parts of the original image and gradually implants with increasing amounts of information based on histogram equalization information. The output from saliency is the perceptible areas within an image, which is the most notable position from the perspective of vision; as a result, any changes made other than those areas will be less noticeable to viewers. Implementing the histogram method helps identify the areas where we can hide our secret information within that image. Using the LSB replacement technique, we adaptively insert our confidential data into the original image. Here, we use the saliency map to find out the non-salient region or less perceptible region to improve the imperceptibility, and the histogram equalization technique is used to maximize the hiding capacity within those less perceptible regions. So that we can improve the imperceptibility as well as the hiding capacity.","PeriodicalId":37046,"journal":{"name":"ECTI Transactions on Computer and Information Technology","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image Watermarking Framework using Histogram Equalization and Visual Saliency\",\"authors\":\"Bishwabara Panda, Manas Ranjan Nayak, Pradeep Kumar Mallick, Abhishek Basu\",\"doi\":\"10.37936/ecti-cit.2023174.252375\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a digital image watermarking strategy using histogram equalization and visual Saliency followed by LSB (Least Significant Bit) replacement for better imperceptibility with hiding capacity. With this technique, a saliency map determines lesser-observable parts of the original image and gradually implants with increasing amounts of information based on histogram equalization information. The output from saliency is the perceptible areas within an image, which is the most notable position from the perspective of vision; as a result, any changes made other than those areas will be less noticeable to viewers. Implementing the histogram method helps identify the areas where we can hide our secret information within that image. Using the LSB replacement technique, we adaptively insert our confidential data into the original image. Here, we use the saliency map to find out the non-salient region or less perceptible region to improve the imperceptibility, and the histogram equalization technique is used to maximize the hiding capacity within those less perceptible regions. So that we can improve the imperceptibility as well as the hiding capacity.\",\"PeriodicalId\":37046,\"journal\":{\"name\":\"ECTI Transactions on Computer and Information Technology\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ECTI Transactions on Computer and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37936/ecti-cit.2023174.252375\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Decision Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ECTI Transactions on Computer and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37936/ecti-cit.2023174.252375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Decision Sciences","Score":null,"Total":0}
Image Watermarking Framework using Histogram Equalization and Visual Saliency
This paper proposes a digital image watermarking strategy using histogram equalization and visual Saliency followed by LSB (Least Significant Bit) replacement for better imperceptibility with hiding capacity. With this technique, a saliency map determines lesser-observable parts of the original image and gradually implants with increasing amounts of information based on histogram equalization information. The output from saliency is the perceptible areas within an image, which is the most notable position from the perspective of vision; as a result, any changes made other than those areas will be less noticeable to viewers. Implementing the histogram method helps identify the areas where we can hide our secret information within that image. Using the LSB replacement technique, we adaptively insert our confidential data into the original image. Here, we use the saliency map to find out the non-salient region or less perceptible region to improve the imperceptibility, and the histogram equalization technique is used to maximize the hiding capacity within those less perceptible regions. So that we can improve the imperceptibility as well as the hiding capacity.