# A Robust Multi-Watermarking Algorithm for Medical Images Based on DTCWT-DCT and Henon Map
## 1 Introduction  
Since the birth of medical imaging technology, medical images that, in the auxiliary diagnosis of the industry, play an increasingly important role in making accurate diagnoses for doctors, include computed tomography (CT) images, X-ray images, ultrasound images, magnetic resonance imaging (MRI) images, electrocardiograms, electroencephalograms, angiography images, radionuclide images etc. generated by medical imaging systems [1]. Especially in recent years, due to the rapid development of life sciences, materials science, robotics engineering and information science, doctors can use imagingsystems that already have microscopic resolution to directly generate medical images, and can even operate nanorobots deep inside patients' bodies to perform molecular-level real-time diagnoses and cancer targeted therapy, according to the micro-camera on the robot and the images returned by various sensors. At present, many hospitals have developed their own smart medical platforms [1; 2]. These platforms facilitate patients' access to electronic medical records and medical images. Some rare and precious medical images stored on such systems also provide valuable technical exchanges and case sharing between doctors and peers. For the convenience of diagnoses, doctors usually embed the personal information of the patient directly in the medical images, which brings many safety hazards for the storage and transmission of medical images. Patients' private information may be leaked or subject to malicious attacks. The use of medical image watermarking (MIW) technology can effectively solve this problem [3; 4]. Digital watermarking was first proposed to protect the copyright of digital multimedia on the Internet. Now we can hide the personal information of patients in the corresponding medical images according to their characteristics so as to protect the privacy of patients, avoid tampering with patients' data, and make sure that such material is transmitted safely on the Internet. But for medical images, unique characteristics must also be taken into account. Such images are an important means for doctors to obtain pathology information about patients. In the medical field, the quality requirements for patients' pathology medical data are extremely strict, and no changes are allowed [5]. Anything that may affect medical pathology data is not advisable. Hence, study of medical image digital watermarking is particularly important [6]. [PERSON] et al. proposed the second-generation watermark algorithm in 1999, which applied image features to watermark embedding and extraction, and gave rise to zero-watermark technology. In recent years, numerous medical watermarking algorithms have been developed. Scholars and experts in various countries have done lots of research on the digital watermarking of medical images. These research algorithms are divided into three categories, each of which will now be summarized. (1) Those based on Region of Non-Interest (RONI); [PERSON] et al. [7] designed a hybrid watermark using bose, ray, hocquenghem (BCH) coding, chaos theory and RRNS in spatial domain, and the RONI was used to embed watermark information; [PERSON] et al. [8] first divided the host medical image, then hid the patient data and the hash values in a Region of Interest (ROI), hid the tamper recovery data and the hash values of tamper detection in RONI. Each embeddable ROI pixel can hide one or two bits to reduce ROI distortion; [PERSON] et al. [9] proposed two different algorithms. By modifying the threshold value, the transform domain coefficient of 8x8 is compared with the size of watermark and Electronic Patients Record (EPR). One algorithm embeds both watermark and EPR into ROI and RONI, and the other keeps the ROI unchanged and hides the watermark and EPR in RONI; [PERSON] et al. [10], using a human visual system (HVS) model to identify the RONI of the cover medical image, explicitly inserted the watermark into the RONI of the cover medical image to obtain a watermarked medical image; [PERSON] et al.