Robust Image Watermarking Based on Psychovisual Threshold

Because of the facility of accessing and sharing digital images through the internet, digital images are often copied, edited and reused. Digital image watermarking is an approach to protect and manage digital images as intellectual property. The embedding of a natural watermark based on the properties of the human eye can be utilized to effectively hide a watermark image. This paper proposes a watermark embedding scheme based on the psychovisual threshold and edge entropy. The sensitivity of minor changes in DCT coefficients against JPEG quantization tables was investigated. A watermark embedding scheme was designed that offers good resistance against JPEG image compression. The proposed scheme was tested under different types of attacks. The experimental results indicated that the proposed scheme can achieve high imperceptibility and robustness against attacks. The watermark recovery process is also robust against attacks

Just noticeable distortion model and its application in image processing

Master'sMASTER OF ENGINEERIN

Localization of just noticeable difference for image compression

The just noticeable difference (JND) is the minimal difference between stimuli that can be detected by a person. The picture-wise just noticeable difference (PJND) for a given reference image and a compression algorithm represents the minimal level of compression that causes noticeable differences in the reconstruction. These differences can only be observed in some specific regions within the image, dubbed as JND-critical regions. Identifying these regions can improve the development of image compression algorithms. Due to the fact that visual perception varies among individuals, determining the PJND values and JND-critical regions for a target population of consumers requires subjective assessment experiments involving a sufficiently large number of observers. In this paper, we propose a novel framework for conducting such experiments using crowdsourcing. By applying this framework, we created a novel PJND dataset, KonJND++, consisting of 300 source images, compressed versions thereof under JPEG or BPG compression, and an average of 43 ratings of PJND and 129 self-reported locations of JND-critical regions for each source image. Our experiments demonstrate the effectiveness and reliability of our proposed framework, which is easy to be adapted for collecting a large-scale dataset. The source code and dataset are available at https://github.com/angchen-dev/LocJND.</p

Localization of Just Noticeable Difference for Image Compression

The just noticeable difference (JND) is the minimal difference between stimuli that can be detected by a person. The picture-wise just noticeable difference (PJND) for a given reference image and a compression algorithm represents the minimal level of compression that causes noticeable differences in the reconstruction. These differences can only be observed in some specific regions within the image, dubbed as JND-critical regions. Identifying these regions can improve the development of image compression algorithms. Due to the fact that visual perception varies among individuals, determining the PJND values and JND-critical regions for a target population of consumers requires subjective assessment experiments involving a sufficiently large number of observers. In this paper, we propose a novel framework for conducting such experiments using crowdsourcing. By applying this framework, we created a novel PJND dataset, KonJND++, consisting of 300 source images, compressed versions thereof under JPEG or BPG compression, and an average of 43 ratings of PJND and 129 self-reported locations of JND-critical regions for each source image. Our experiments demonstrate the effectiveness and reliability of our proposed framework, which is easy to be adapted for collecting a large-scale dataset. The source code and dataset are available at https://github.com/angchen-dev/LocJND

Perceptual Video Quality Assessment and Enhancement

With the rapid development of network visual communication technologies, digital video has become ubiquitous and indispensable in our everyday lives. Video acquisition, communication, and processing systems introduce various types of distortions, which may have major impact on perceived video quality by human observers. Effective and efficient objective video quality assessment (VQA) methods that can predict perceptual video quality are highly desirable in modern visual communication systems for performance evaluation, quality control and resource allocation purposes. Moreover, perceptual VQA measures may also be employed to optimize a wide variety of video processing algorithms and systems for best perceptual quality. This thesis exploits several novel ideas in the areas of video quality assessment and enhancement. Firstly, by considering a video signal as a 3D volume image, we propose a 3D structural similarity (SSIM) based full-reference (FR) VQA approach, which also incorporates local information content and local distortion-based pooling methods. Secondly, a reduced-reference (RR) VQA scheme is developed by tracing the evolvement of local phase structures over time in the complex wavelet domain. Furthermore, we propose a quality-aware video system which combines spatial and temporal quality measures with a robust video watermarking technique, such that RR-VQA can be performed without transmitting RR features via an ancillary lossless channel. Finally, a novel strategy for enhancing video denoising algorithms, namely poly-view fusion, is developed by examining a video sequence as a 3D volume image from multiple (front, side, top) views. This leads to significant and consistent gain in terms of both peak signal-to-noise ratio (PSNR) and SSIM performance, especially at high noise levels

Comparative evaluation of video watermarking techniques in the uncompressed domain

Thesis (MScEng)--Stellenbosch University, 2012.ENGLISH ABSTRACT: Electronic watermarking is a method whereby information can be imperceptibly embedded into electronic media, while ideally being robust against common signal manipulations and intentional attacks to remove the embedded watermark. This study evaluates the characteristics of uncompressed video watermarking techniques in terms of visual characteristics, computational complexity and robustness against attacks and signal manipulations. The foundations of video watermarking are reviewed, followed by a survey of existing video watermarking techniques. Representative techniques from different watermarking categories are identified, implemented and evaluated. Existing image quality metrics are reviewed and extended to improve their performance when comparing these video watermarking techniques. A new metric for the evaluation of inter frame flicker in video sequences is then developed. A technique for possibly improving the robustness of the implemented discrete Fourier transform technique against rotation is then proposed. It is also shown that it is possible to reduce the computational complexity of watermarking techniques without affecting the quality of the original content, through a modified watermark embedding method. Possible future studies are then recommended with regards to further improving watermarking techniques against rotation.AFRIKAANSE OPSOMMING: ’n Elektroniese watermerk is ’n metode waardeur inligting onmerkbaar in elektroniese media vasgelê kan word, met die doel dat dit bestand is teen algemene manipulasies en doelbewuste pogings om die watermerk te verwyder. In hierdie navorsing word die eienskappe van onsaamgeperste video watermerktegnieke ondersoek in terme van visuele eienskappe, berekeningskompleksiteit en weerstandigheid teen aanslae en seinmanipulasies. Die onderbou van video watermerktegnieke word bestudeer, gevolg deur ’n oorsig van reedsbestaande watermerktegnieke. Verteenwoordigende tegnieke vanuit verskillende watermerkkategorieë word geïdentifiseer, geïmplementeer en geëvalueer. Bestaande metodes vir die evaluering van beeldkwaliteite word bestudeer en uitgebrei om die werkverrigting van die tegnieke te verbeter, spesifiek vir die vergelyking van watermerktegnieke. ’n Nuwe stelsel vir die evaluering van tussenraampie flikkering in video’s word ook ontwikkel. ’n Tegniek vir die moontlike verbetering van die geïmplementeerde diskrete Fourier transform tegniek word voorgestel om die tegniek se bestandheid teen rotasie te verbeter. Daar word ook aangetoon dat dit moontlik is om die berekeningskompleksiteit van watermerktegnieke te verminder, sonder om die kwaliteit van die oorspronklike inhoud te beïnvloed, deur die gebruik van ’n verbeterde watermerkvasleggingsmetode. Laastens word aanbevelings vir verdere navorsing aangaande die verbetering van watermerktegnieke teen rotasie gemaak

High Dynamic Range Visual Content Compression

This thesis addresses the research questions of High Dynamic Range (HDR) visual contents compression. The HDR representations are intended to represent the actual physical value of the light rather than exposed value. The current HDR compression schemes are the extension of legacy Low Dynamic Range (LDR) compressions, by using Tone-Mapping Operators (TMO) to reduce the dynamic range of the HDR contents. However, introducing TMO increases the overall computational complexity, and it causes the temporal artifacts. Furthermore, these compression schemes fail to compress non-salient region differently than the salient region, when Human Visual System (HVS) perceives them differently. The main contribution of this thesis is to propose a novel Mapping-free visual saliency-guided HDR content compression scheme. Firstly, the relationship of Discrete Wavelet Transform (DWT) lifting steps and TMO are explored. A novel approach to compress HDR image by Joint Photographic Experts Group (JPEG) 2000 codec while backward compatible to LDR is proposed. This approach exploits the reversibility of tone mapping and scalability of DWT. Secondly, the importance of the TMO in the HDR compression is evaluated in this thesis. A mapping-free post HDR image compression based on JPEG and JPEG2000 standard codecs for current HDR image formats is proposed. This approach exploits the structure of HDR formats. It has an equivalent compression performance and the lowest computational complexity compared to the existing HDR lossy compressions (50% lower than the state-of-the-art). Finally, the shortcomings of the current HDR visual saliency models, and HDR visual saliency-guided compression are explored in this thesis. A spatial saliency model for HDR visual content outperform others by 10% for spatial visual prediction task with 70% lower computational complexity is proposed. Furthermore, the experiment suggested more than 90% temporal saliency is predicted by the proposed spatial model. Moreover, the proposed saliency model can be used to guide the HDR compression by applying different quantization factor according to the intensity of predicted saliency map