Abstract: A face image processing method is applied to an electronic device, such that the electronic device can perform a face detection to a digital image to obtain a face image in the digital image automatically, and perform a skin color detection to the face image to exclude non-skin features such as eyes, eyeglasses, eyebrows, a moustache, a mouth and nostrils on the face image, and form a skin mask in an area range of the face image belonging to skin color, and finally perform a filtering process to the area range of the face image corresponding to the skin mask to filter high-frequency, mid-frequency and low-frequency noises of an abnormal skin color in the area range of the face image, so as to quickly remove blemishes and dark spots existed in the area range of the face image.

Abstract: A method for estimating noise according to a multiresolution model is applied to an imaging device and comprises steps of: using an imaging sensor of the imaging device to capture a series of images of a scene under different imaging conditions; processing the images with a multiresolution transformation process to obtain a series of sub-images corresponding to different frequency layers; processing a series of the sub-images of the images that are in a same frequency layer to generate an averaged image; determining a difference between each of the sub-images in the same frequency layer and the averaged image corresponding to that frequency layer, and calculating the differences and the averaged image to obtain noise level functions of the imaging sensor in the different frequency layers under the different imaging conditions; and defining the noise level functions of the imaging sensor as noise samples for establishing an a priori model database.

Abstract: A face image processing method is applied to an electronic device, such that the electronic device can perform a face detection to a digital image to obtain a face image in the digital image automatically, and perform a skin color detection to the face image to exclude non-skin features such as eyes, eyeglasses, eyebrows, a moustache, a mouth and nostrils on the face image, and form a skin mask in an area range of the face image belonging to skin color, and finally perform a filtering process to the area range of the face image corresponding to the skin mask to filter high-frequency, mid-frequency and low-frequency noises of an abnormal skin color in the area range of the face image, so as to quickly remove blemishes and dark spots existed in the area range of the face image.

Abstract: A method for estimating noise according to a multiresolution model is applied to an imaging device and comprises steps of: using an imaging sensor of the imaging device to capture a series of images of a scene under different imaging conditions; processing the images with a multiresolution transformation process to obtain a series of sub-images corresponding to different frequency layers; processing a series of the sub-images of the images that are in a same frequency layer to generate an averaged image; determining a difference between each of the sub-images in the same frequency layer and the averaged image corresponding to that frequency layer, and calculating the differences and the averaged image to obtain noise level functions of the imaging sensor in the different frequency layers under the different imaging conditions; and defining the noise level functions of the imaging sensor as noise samples for establishing an a priori model database.