Abstract:
A fast method of color interpolation of pixels of an image acquired by a color filtered digital sensor uses a very simple cost function that nevertheless produce interpolated images of good quality. The cost function is computationally simpler because it does not require the calculation of powers and square roots. An efficient triangulation algorithm that may be executed in far less time than prior art triangulation processes, while practically ensuring the same performances. The peculiarity of this triangulation algorithm consists in that on average it requires only two iteration steps, while the most accurate prior triangulation algorithm is completed only after four iteration steps. Optionally, the interpolation process may be followed by an anti-aliasing processing that effectively removes color artifacts that may be created during the interpolation process.
Abstract:
A particularly efficient and simple method for Bayer color filter array (CFA) compression requires practically negligible computational complexity and external memory requirement while yielding a substantially lossless performance of the compression-decompression processes. For each color channel, the process comprises the step of
gathering Bayer pattern pixel values by pairs, each pair being composed by two successive pixels belonging to the channel along the scanning direction of the pixels of the image, thus each pair of values representing a current input vector; calculating a predictor vector of the input vector in terms of the differences between the values defining the input vector and a pair of prediction values generated according to a certain criterion, for representing a prediction error; quantizing each so calculated predictor vector according to a heavier or lighter degree of quantization depending on whether the predictor vector is representative of an area of relatively uniform color of the image or of an area of relatively abrupt changes of colors of the image; generating a multibit code representative of the quantized predictor vector of the input vector according to a certain compression ratio.
Abstract:
Described herein is a method for block coding of a flow (I) of data, in particular video data, via a compression operation (100; 200; 300) that comprises: applying to input-data blocks (B, CB; MB) in said data flow (I) a discrete-cosine-transform (DCT) operation (120; 220) and a quantization operation (130; 230) to produce compressed-data blocks (DB); subjecting said compressed-data blocks (DB) to a coding operation (235, 240) to obtain compressed output flows (O); and moreover applying an inverse-quantization operation (190; 290) and an inverse-discrete-cosine-transform (IDCT) operation (195; 295) on said compressed-data blocks (DB) to obtain reconstructed blocks (RB). The method envisages controlling (1000; 1100) generation of mismatch errors from said input-data blocks (B, CB; MB) via the operations of:
detecting from said input-data blocks (B, CB; MB) and compressed-data blocks (DB) data blocks (DB; MB) that are liable to cause mismatch errors; and modifying said block (DB; MB) that are liable to cause mismatch errors prior to said coding operation (235, 240).
Abstract:
Subdivision per basic color channels of grey level data generated by a color sensor is no longer required according to a novel color interpolation method of an image acquired by a digital color sensor generating grey levels for each image pixel in function of the filter applied to the sensor, by interpolating the values of missing colors of each image pixel for generating triplets or pairs of values of primary colors (RGB) or complementary hues for each image pixel. The method comprises the following steps:
i) calculating spatial variation gradients of primary colors or complementary hues for each image pixel and storing the information of directional variation of primary color or complementary hue in look-up tables pertaining to each pixel; ii) interpolating color values of each image pixel considering said directional variation information of the respective values of primary colors or complementary hues stored in the respective look-up tables of the pixel for generating said multiple distinct values for each image pixel.
Abstract:
A method for image compression of a set of image data (I) includes operating a quantization operation (20; 150; 230) on the image data (I), said quantization operation (20; 150; 230) including controlling a compression factor by applying a scaled quantization level ( ), obtained by multiplying a first quantization level (Q) by a gain factor (G; Gs; Gi), the gain factor (G; Gs; Gi) being updated (100; 1000; 110; 300) as a function of a bit per pixel value (bpp) of a compressed image (O). The update operation (1000; 110; 300) includes an iterative procedure (110) comprising at least one iteration step (Eq. 6; Eq. 7) that provides for updating a current gain factor (G n+1 ) as a function of a previous gain (G n ) used for performing a previous compression step and as a function of a ratio (G n ) of the bit per pixel value (bpp) of the compressed image (O) at the previous compression step to a target bit per pixel value (T). Preferred application is in Joint Photographic Experts Group (JPEG) and digital still cameras.