## 1 Introduction  
Underwater wireless optical communication (UWOC) has gained a lot of interest over the past few years, and provides better security, lower time delay, higher bandwidth [1], and is more compatible with underwater ecosystems. Generally, there are two main types of light receivers that can be used for UWOC: photo detectors (PD) and image sensors. Most existing UWOC systems utilize PDs as the receivers due to their high reception bandwidth and response speed and because they can achieve an extremely high data rate [2]. On the contrary, in the past, image sensors were not widely adopted by academia due to their high price, low resolution, and low achievable data rate. But in recent years, with the great leap with regard to price and performance of image sensor technology, the vast majority of underwater detection equipment has built-in high-resolution image sensors. This motivates the development of underwater optical camera communication (UOCC), which offers a more flexible and convenient way to achieve UWOC [3]. In [4, 5], a global shutter (GS)-based UOCC is demonstrated with the limited data rate of 100 bps and 750 bps at a distance of 1 m. The extremely low data rate in bps, which is mainly restricted by the frame rate in GS mode, is difficult to use in real scenes. Therefore, the current UOCC system has much room for improvement compared to the data rate in terms of Kbps of land OCC. On the other hand, the rolling shutter effect (RSE) of a complementary metal-oxide semiconductor (CMOS) image sensor is widely adopted in land OCC to receive multiple bits modulated at a high frequency within one frame and improve the transmission rate [6, 7, 8, 9, 10, 11]. However, to our best knowledge, RSE-based OCC has not been well investigated in underwater environments. In addition, it is worth noting that the experimental scene shown in [4; 5] is a static water channel. Nevertheless, in a practical underwater channel, due to the breaking surface waves and rain, air bubbles are created in the water that induce severe performance degradation and cause significant optical attenuation [12]. When the optical signal propagates through the bubbly underwater channel, reflection and refraction occur at the interface of each bubble [13; 14]. The light strays into different directions, causing severe attenuation of light intensity and phase overlap. In [15; 16; 17], the performances of PD-based UWOC in the presence of air bubbles was studied, and several statistical models were proposed to characterize turbulence-induced fading in bubbly UWOC channels. However, no method was given to eliminate the serious impact of bubbles on optical signal attenuation in these publications. Beam expansion could help mitigate the performance degradation due to the deep fade caused by air bubble scatters [18]. However, this would lead to greater transmission power requirements and higher hardware costs while improving performance would be limited. As mentioned above, it is still difficult to find a scheme to deal with bubbles of various sizes and densities quickly and effectively in the existing works. Another obstacle for rolling shutter effect (RSE)-based OCC is sampling point offset (SPO), which refers to the inconsistency between sampling point and pulse position due to the deviation of clock recovery (CR). When it comes to the decoding process of an RSE-based-OCC system, conventional CR based on a synchronization head is widely used [19]. After the received data is processed with a threshold scheme, sampling is required to extract the binary signal. Generally, the sampling interval is estimated with a synchronization head. However, due to the influence of various noises, such as the noise from ambient light as well as the thermal noise and shot noise of the CMOS image sensor, the length of binary fringes may deviate from the theoretical sampling interval in some positions, resulting in the confusion of subsequent sampling and a high bit error rate (BER).