Image expansion is an interpolation problem which has been known to cause blurred and jagged edges. A number of methods have been developed to preserve sharp edges while preventing jaggedness, but the results are often unsatisfactory. In this paper, we propose an image expansion technique which can preserve sharpness of an image without jagged edges, while maintaining smoothness in other parts of the interpolated image. The input image is first expanded by the nearest neighbour interpolation method in order to preserve the original edges. It is also interpolated by another interpolation algorithm with a different degree of edge preservation. The absolute difference between the two outputs produces a residual image of edges with a magnitude which increases with the sharpness of an original edge. This edge residual image is then used to adaptively adjust the gamma value of a novel modified gamma contrast enhancement algorithm so that the edges can regain their original sharpness. A halo effect suppressor has also been introduced to suppress halo effects by avoiding over-sharpening of the edges. It has been shown that our algorithm can produce sharp images without jagged edges and outperform the other benchmarking algorithms visually and quantitatively.

For color images captured by single-image sensors, enhancement is usually performed after Color Filter Array (CFA) demosaicking due to the fact that most image enhancement algorithms are developed for full color images. As enhancement prior to demosaicking will produce a different result from enhancement after demosaicking, it will be more desirable to enhance an image prior to demosaicking particularly for images with a narrow intensity range. One reason is that demosaicking is the interpolation of missing colors, and interpolation within a narrow intensity range with only a few discrete intensity levels may lead to large interpolation errors. On the other hand, if enhancement is performed prior to demosaicking to widen the range of intensity, the above-mentioned interpolation errors could be reduced. In this paper, we proposed an image enhancement algorithm particularly for CFA images prior to demosaicking. It has been shown that enhancement prior to demosaicking could produce more visually pleasing images than those performed after demosaicking.

Color artifacts are often found at edges due to interpolation across them. To tackle this problem, four high-order interpolants for four different directions are determined, and a weight based on the corresponding absolute directional color differences is assigned to each of them. In a smooth area, the interpolants in the four directions will have equal normalized weights of 1/4. In a nonsmooth area with a sharp edge, the normalized weights for the interpolants on the opposite side of an edge will be small and less than 1/4, but this inclusion will still manifest itself as color artifacts in the output image. In our proposed method, the frequency distribution of the weights for the entire image is first determined. To reduce color artifacts, the weights are hard thresholded such that any weights below a threshold are set to zero, and that optimal threshold is determined according to the frequency distribution of the directional color differences. A detail-preserving median based multishell filter is then applied to the fully demosaicked green channel to prune outliers resulting from high-order interpolation of thin features. Based on the experimental results, it has been shown that our proposed algorithm outperforms the other algorithms with minimal color artifacts for various types of images.

For image contrast enhancement, an S-shaped transfer function has been developed to better match the human vision system with an associated median brightness subtraction and addition method to preserve the median brightness of an image. However, this median brightness preservation method will cause clipping of the dynamic range of images resulting in a loss of contrast. Moreover, preserving the mean or median image brightness will sometimes produce a different result without a consistent preference. In this letter, we have developed a method to preserve either the mean or median image brightness by shifting the intersection point of S-shaped curves along the y = x line by successive approximation. To improve computational efficiency, two newly derived equations have been proposed to reduce the number of optimum control parameters from four to two for solving the S-shaped curves. In addition, our proposed method can alter the image brightness without causing clipping at either ends of the intensity range. Our proposed brightness preservation method can also be applied to a video sequence to change its brightness without causing any flickering. It has been shown that our proposed method can produce visually pleasing enhanced images and videos.

Demosaicing is the process of interpolating the output from a single chip colour filter array sensor to form a full colour image. In hardware, the simplest algorithms: zero order hold and bilinear interpolation, are commonly used because of their simplicity and low resource requirements. State of the art algorithms are difficult to implement in hardware because of their complex access patterns. This paper explores the streamed implementation of a higher order interpolation filter, with a weighted median classifier. Although this comes at a cost of a factor of 10 increase in hardware resources, and a reduction in maximum pixel clock frequency by 30%, this state of the art algorithm gives considerably improved images of 11.2 dB in peak signal to noise ratio with a considerable reduction in interpolation artifacts. For real-time applications where image quality is critical, an implementation of such an advanced demosaicing algorithm on FPGA is essential.

Demosaicking is an estimation process to determine missing color values when a single-sensor digital camera is used for color image capture. In this paper, we propose a number of new methods based on the application of Taylor series and cubic spline interpolation for color filter array demosaicking. To avoid the blurring of an edge, interpolants are first estimated in four opposite directions so that no interpolation is carried out across an edge. A weighted median filter, whose filter coefficients are determined by a classifier based on an edge orientation map, is then used to produce an output from the four interpolants to preserve edges. Using the proposed methods, the original color can be faithfully reproduced with minimal amount of color artifacts even at edges.

When a single image sensor is used to capture colour images, only one colour value is acquired at each pixel location. Colour filter array (CFA) demosaicking refers to the estimation of the other two missing colour values in order to produce a full colour image. In this paper, we have shown that cubic spline interpolation is suitable for CFA demosaicking for producing a smooth colour image due to the known fact that it can generate a smooth curve to fit a set of data points. In our approach to obtain a unique solution for cubic spline interpolation, the two required extra conditions were derived based on the correlation between colour planes. Our proposed method, by applying cubic spline interpolation in conjunction with a selector based on edge orientation, has been shown to outperform other existing demosaicking methods.

It is shown that for a particular window size, by changing gradually the minimum and maximum operators to the higher and lower order statistics of the shell, respectively, the multi-shell median filter will gradually turn from a multistage max/median filter into a 2-D standard median filter.

The multi-shell median filters have been shown to be effective in preserving image details as well as in the suppression of impulsive noise. In this paper, the statistical analysis of a general class of median based multi-shell order-statistics filters is presented. Using statistical threshold decomposition, together with a tri-tree structure, the statistical properties of the filters were derived. Based on the results, a 2-D nonlinear filter which is of good compromise between noise attenuation and detail preservation to fit various applications can be obtained.>