In this study, we address the emerging necessity of converting Standard Dynamic Range Television (SDRTV) content into High Dynamic Range Television (HDRTV) in light of the limited number of native HDRTV content. A principal technical challenge in this conversion is the exacerbation of coding artifacts inherent in SDRTV, which detrimentally impacts the quality of the resulting HDRTV. To address this issue, our method introduces a novel approach that conceptualizes the SDRTV-to-HDRTV conversion as a composite task involving dual degradation restoration. This encompasses inverse tone mapping in conjunction with video restoration. We propose Dual Inversion Downgraded SDRTV to HDRTV Network (DIDNet), which can accurately perform inverse tone mapping while preventing encoding artifacts from being amplified, thereby significantly improving visual quality. DIDNet integrates an intermediate auxiliary loss function to effectively separate the dual degradation restoration tasks and efficient learning of both artifact reduction and inverse tone mapping during end-to-end training. Additionally, DIDNet introduces a spatio-temporal feature alignment module for video frame fusion, which augments texture quality and reduces artifacts. The architecture further includes a dual-modulation convolution mechanism for optimized inverse tone mapping. Recognizing the richer texture and high-frequency information in HDRTV compared to SDRTV, we further introduce a wavelet attention module to enhance frequency features. Our approach demonstrates marked superiority over existing state-of-the-art techniques in terms of quantitative performance and visual quality.

翻译：本研究针对原生高动态范围电视（HDRTV）内容数量有限这一现状，探讨了将标准动态范围电视（SDRTV）内容转换为HDRTV的新兴需求。该转换中的关键技术挑战在于，SDRTV固有的编码伪影会被放大，从而对生成的HDRTV质量造成不利影响。为解决此问题，本文提出一种新方法，将SDRTV到HDRTV的转换概念化为涉及双退化复原的复合任务，该任务包含逆色调映射与视频复原环节。我们提出了双逆降级SDRTV到HDRTV网络（DIDNet），该网络能在防止编码伪影放大的同时精确执行逆色调映射，从而显著提升视觉质量。DIDNet集成了一个中间辅助损失函数，以有效分离双退化复原任务，并在端到端训练中同时实现伪影减少和逆色调映射的高效学习。此外，DIDNet引入了一个用于视频帧融合的时空特征对齐模块，以增强纹理质量并减少伪影。该架构还包含一个双调制卷积机制，用于优化逆色调映射。针对HDRTV相较于SDRTV包含更丰富纹理和高频信息的特点，我们进一步引入了一个小波注意力模块以增强频率特征。本方法在定量性能和视觉质量方面均显著优于现有最先进技术。