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Currently, high dynamic range (HDR) videos with high resolution (HR) have become popular due to the display and the rendered technological advancements. However, making ultra-high definition (UHD) with HDR videos is expensive. The legacy low-resolution (LR) standard dynamic range (SDR) format is still largely used in practice. It is necessary to search for a solution to transform LR SDR videos into UHD HDR format. In this paper, we consider joint super resolution and learning inverse tone mapping an issue of high-frequency reconstruction and local contrast enhancement, and we propose an architecture based on a generative adversarial network to apply joint SR-ITM learning. Specifically, we include the residual ResNeXt block (RRXB) as a basic module to better capture high-frequency textures and adopt YUV interpolation to achieve local contrast enhancement. By adopting a generative adversarial network as a pivotal training mechanism, our designs show advantages in both integration and performance. Our code is now available on GitHub: SR-ITM-GAN.

Holothurian counting is a basic requirement in aquaculture. An in situ noncontact approach for holothurian counting is basically harmless, which makes such techniques an optimal choice for aquaculture monitoring. To develop an in situ noncontact counting system, there are two main challenges. In the underwater environment, the light is absorbed by the water, which distorts the underwater image color. Another challenge comes from the dynamic background, which makes it difficult to associate the ID to each holothurian. In this paper, we propose an effective usual framework for holothurian counting. The framework is composed of three modules: an underwater enhancement module, a multiple object detection module and a multiple object tracking module. To evaluate our system comprehensively, we collect and release the first underwater multiple object tracking dataset following the same format as MOT-16. The results show that our system can practically detect, track and count holothurians under different conditions.