Dark channel enhancement research on human ear images based on smartphone photography

• Published in: Concurrency and computation 2024-10, Vol.36 (22), p.n/a
• Main Authors: Lu, Dongxin, Zheng, Danni, Kou, Lei, Li, Qingfeng, Ke, Wende
• Format: Article
• Language: English
• Subjects: Algorithms; Cellular telephones; Diagnosis; diagnosis and treatment; Ear; ears; enhancement; haze removal; Image contrast; Image enhancement; Image quality; Insomnia; Massaging; Medical imaging; Patients; Physicians; Preprocessing
• ISSN: 1532-0626; 1532-0634
• DOI: 10.1002/cpe.8216

Summary The experienced doctors can alleviate symptoms such as headaches, insomnia, anxiety, and depression by observing the patient's ears and massaging specific areas. In order to achieve remote ear condition diagnosis and guide patients to massage their ears independently through the network, patients can use their mobile phones to take and send photos of ears to doctors. However, due to significant differences in the clarity of photos taken by different mobile phones, as well as susceptibility to haze, lighting, jitter, and low pixels, the quality of photos is poor, which affects the accuracy of remote diagnosis by doctors. This study adopted an image preprocessing method based on He Kaiming's dark channel prior dehazing method to enhance the original ear images captured by mobile phones. The dehazing algorithm was used to remove the haze effect of the ear images, improving image quality and contrast, making the wrinkles, protrusions, pigmentation and other areas of the ear more obvious. The experiment has showed the comparison by adjusting weight from 15% to 95% between two methods—dark channel prior method and the dark channel prior method after preprocessing, which has proven the effectiveness of dehazing method in human ear images taken by mobile phones. The image quality after preprocessing and dehazing is widely recognized and accepted by doctors at hospitals in Hangzhou, China.