Editorial Advancements in Learning-Based Quality Prediction for Advanced Visual Media

IF 8.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Sebastian Bosse
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引用次数: 0

Abstract

In this special issue of the IEEE Journal of Selected Topics in Signal Processing , we delve into the burgeoning domain of Learning-Based Quality Prediction for Advanced Visual Media. The rapid proliferation of advanced visual media modalities, such as high dynamic range and mixed reality, has not only enhanced interactive and immersive user experiences but has also posed significant challenges in the realm of quality assessment and optimization. This issue collates pioneering research that addresses these challenges, underscoring the critical role of human perception in the acceptance and success of such applications.
基于学习的高级视觉媒体质量预测的编辑进展
在本期《IEEE 信号处理选题期刊》特刊中,我们将深入探讨基于学习的高级视觉媒体质量预测这一新兴领域。高动态范围和混合现实等先进视觉媒体模式的迅速普及,不仅增强了交互式和沉浸式用户体验,也给质量评估和优化领域带来了重大挑战。本期杂志汇集了应对这些挑战的开创性研究,强调了人类感知在此类应用的接受和成功中的关键作用。
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来源期刊
IEEE Journal of Selected Topics in Signal Processing
IEEE Journal of Selected Topics in Signal Processing 工程技术-工程:电子与电气
CiteScore
19.00
自引率
1.30%
发文量
135
审稿时长
3 months
期刊介绍: The IEEE Journal of Selected Topics in Signal Processing (JSTSP) focuses on the Field of Interest of the IEEE Signal Processing Society, which encompasses the theory and application of various signal processing techniques. These techniques include filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals using digital or analog devices. The term "signal" covers a wide range of data types, including audio, video, speech, image, communication, geophysical, sonar, radar, medical, musical, and others. The journal format allows for in-depth exploration of signal processing topics, enabling the Society to cover both established and emerging areas. This includes interdisciplinary fields such as biomedical engineering and language processing, as well as areas not traditionally associated with engineering.
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