NovelIQA 2024 : Novel Approaches to Image Quality Assessment

Dear Colleagues,

In the ever-evolving landscape of digital imaging, the demand for accurate and meaningful evaluation of image quality resonates across diverse applications, from medical diagnostics to social media. The importance of robust Image Quality Assessment (IQA) methodologies cannot be overstated in this context. This Special Issue serves as a pivotal platform for showcasing cutting-edge research, driving forward our understanding and methodologies for appraising the perceptual quality of images in an ever-evolving landscape.

Within this collection, articles explore groundbreaking concepts that transcend traditional paradigms, delving into the dichotomy between opinion-aware and unaware IQA. Recognizing the inherent subjectivity in human perception, models that account for this subjectivity are emphasized. Furthermore, the issue addresses the imperative for explainable IQA, enhancing trustworthiness and adoption in real-world applications through improved interpretability of assessment models.

Embracing the dynamism of the field, this Special Issue tackles challenges through innovative lenses, spanning multi-modal IQA, contrastive learning strategies, and self-supervised approaches. Streamlining the assessment process with a focus on efficiency is a key objective, while personalized IQA strategies acknowledge the variability in individual preferences and perceptual thresholds.

Encompassing the evaluation of images generated through various means, from synthesized to enhanced, this issue reflects the breadth of contemporary imaging technologies. With a comprehensive exploration of these areas, we aim to lay the foundation for the future of IQA research, offering insights into emerging challenges and opportunities. The confluence of these novel approaches not only enhances our ability to quantify image quality but also propels the field towards a more nuanced and adaptive era of visual perception assessment.

We invite contributions presenting techniques that will shape the future roadmap of IQA, including methods, tools, and ideas contributing to significantly innovative objectives. Scientifically founded innovative and speculative research lines are welcomed for proposal and evaluation, as we collectively strive to advance the frontier of IQA techniques.

Topics of Interest:
- Image and video quality assessment:
- Full-/Reduced-/No- Reference quality assessment;
- Multi-modal quality assessment;
- Generated content quality assessment.
- Aesthetic assessment of image:
- Personalized aesthetic assessment;
- Multi-modal aesthetic assessment.
- Image enhancement.
- Image/Video memorability assessment.
- Image/Video sentiment analysis.

Keywords
- image quality assessment
- opinion aware/unaware image quality assessment
- explainable image quality assessment
- multi-modal image quality assessment
- contrastive learning for image quality assessment
- self-supervised for image quality assessment
- efficient image quality assessment
- image quality assessment for image enhancement
- image quality assessment of synthetized/generated images
- personalized image quality assessment


Dr. Luigi Celona
Dr. Hanhe Lin
Guest Editors