Discrete Wavelet Transform on Color Picture Interpolation of Digital Still Camera

Many people use digital still cameras to take photographs in contemporary society. Significant amounts of digital information have led to the emergence of a digital era. Because of the small size and low cost of the product hardware, most image sensors use a color filter array to obtain image information. However, employing a color filter array results in the loss of image information; thus, a color interpolation technique must be employed to retrieve the original picture. Numerous researchers have developed interpolation algorithms in response to various image problems. The method proposed in this study involves integrating discrete wavelet transform (DWT) into the interpolation algorithm. The method was developed based on edge weight and partial gain characteristics and uses the basic wavelet function to enhance the edge performance and processes of the nearest or larger and smaller direction gradients. The experiment results were compared to those of other methods to verify that the proposed method can improve image quality. 1. Introduction The basic principles of digital still cameras and traditional cameras are analogous. Traditional cameras use sensitization negatives to sense the input image. Digital still cameras project the input image onto a charge-coupled device (CCD), where it is transformed into a digital signal. The digital signal is then stored in a memory component after compression. However, this signal indicates the light intensity and not the color variation. Therefore, a color filter array must be employed for digital sampling. Color filter arrays typically employ the RGB original color separation technique, where red, green, and blue values are mixed into a complete color image after the original image is passed through three color filter arrays. Because of the high costs and large space required to use three color filter arrays with CCDs, only one color filter array with a CCD is employed. Consequently, each pixel possesses only one red, green, and blue color elements. The general color filter array in digital still cameras possesses a Bayer pattern [1], as shown in Figure 1. An interpolation algorithm must be employed to identify the two missing colors based on the surrounding pixels. The zipper effect or false colors are typically observed in images after interpolation. Numerous interpolation algorithms have been proposed to resolve these problems and obtain good image quality. Figure 1: Bayer pattern color filter array. Image interpolation methods possess spatial and frequency characteristics. Edge direction and nonedge