Quantization (image processing)

About: Quantization (image processing) is a research topic. Over the lifetime, 7977 publications have been published within this topic receiving 126632 citations.

IPAD: Intensity Potential for Adaptive De-Quantization.

Abstract: Display devices at bit depth of 10 or higher have been mature but the mainstream media source is still at bit depth of eight. To accommodate the gap, the most economic solution is to render source at low bit depth for high bit-depth display, which is essentially the procedure of de-quantization. Traditional methods, such as zero-padding or bit replication, introduce annoying false contour artifacts. To better estimate the least-significant bits, later works use filtering or interpolation approaches, which exploit only limited neighbor information, cannot thoroughly remove the false contours. In this paper, we propose a novel intensity potential (IP) field to model the complicated relationships among pixels. The potential value decreases as the spatial distance to the field source increases and the potentials from different field sources are additive. Based on the proposed IP field, an adaptive de-quantization procedure is then proposed to convert low-bit-depth images to high-bit-depth ones. To the best of our knowledge, this is the first attempt to apply potential field for natural images. The proposed potential field preserves local consistency and models the complicated contexts well. Extensive experiments on natural, synthetic, and high-dynamic range image data sets validate the efficiency of the proposed IP field. Significant improvements have been achieved over the state-of-the-art methods on both the peak signal-to-noise ratio and the structural similarity.

Picture encoding and/or decoding method and apparatus

Abstract: A picture encoding and/or decoding system adaptively changes encoding manner in discrete cosine transformation or predictive coding for improving a picture quality of transmission picture. A variable length coding method is changed in accordance with the change between the discrete cosine transformation and predictive coding. When discrete cosine transforming, a combination of a zero run length and a pixel value is effected two dimensional variable length coding. When predictive coding, a combination of a zero run length and a difference value between pixel values is effected two dimensional variable length coding. When predictive coding, a predictive value of a block and a quantization width are transmitted.

Carving Orphaned JPEG File Fragments

Abstract: File carving techniques allow for recovery of files from storage devices in the absence of any file system metadata. When data are encoded and compressed, the current paradigm of carving requires the knowledge of the compression and encoding settings to succeed. In this paper, we advance the state of the art in JPEG file carving by introducing the ability to recover fragments of a JPEG file when the associated file header is missing. To realize this, we examined JPEG file headers of a large number of images collected from Flickr photo sharing site to identify their structural characteristics. Our carving approach utilizes this information in a new technique that performs two tasks. First, it decompresses the incomplete file data to obtain a spatial domain representation. Second, it determines the spatial domain parameters to produce a perceptually meaningful image. Recovery results on a variety of JPEG file fragments show that given the knowledge of Huffman code tables, our technique can very reliably identify the remaining decoder settings for all fragments of size 4 KiB or above. Although errors due to detection of image width, placement of image blocks, and color and brightness adjustments can occur, these errors reduce significantly when fragment sizes are >32 KiB.

Image encoding apparatus and quantization characteristics determining apparatus

Abstract: Images are to be efficiently and easily encoded while suppressing block distortion and pseudo-contour generation. A quantization characteristics determining unit receives pixel values from a pixel value input unit, measures the length S of the consecutive occurrence of the same pixel values in connection with a pixel to be encoded and the pixel value differences D, and determines quantization characteristics n with reference to the result of sensory evaluation. A quantization/inverse quantization unit quantizes pixel values to be inputted with the quantization characteristics n, and further inverse quantizes them to reduce the number of gray-scale levels. The output pixel values of the quantization/inverse quantization unit are encoded and outputted by an entropy encoding unit.