Chroma variations and perceived quality of color images of natural scenes

Fedorovskaya, Elena A.; Ridder, Huib de; Blommaert, Frans J. J.

doi:10.1002/(sici)1520-6378(199704)22:2<96::aid-col5>3.0.co;2-z

Cited by 100 publications

(36 citation statements)

References 3 publications

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“…Manipulating the chroma value in the CIELuv colorspace per pixel of the natural image, however, resulted in a systematic deviation between image quality and naturalness judgements. 4,8,9,10,11 Image quality judgements were shifted to higher chroma values relative to the naturalness judgements. In other words, people preferred images that were more colorful than the original although they realized that these images looked somewhat unnatural.…”

Section: Introductionmentioning

confidence: 97%

“…Besides the depth manipulation, we also varied the chroma value per pixel of the originals, creating more and less colorful images. With this manipulation we tried to replicate the shift between image quality and naturalness, as found on monoscopic images, 4,8,9,10,11 for stereoscopic images. Additionally, we determined whether people use similar considerations when evaluating color manipulated 3D as when assessing color manipulated 2D images.…”

Section: Introductionmentioning

confidence: 99%

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Influence of chroma variations on naturalness and image quality of stereoscopic images

Kuijsters

IJsselsteijn

Lambooij

et al. 2009

Human Vision and Electronic Imaging XIV

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The computational view on image quality of Janssen and Blommaert states that the quality of an image is determined by the degree to which the image is both useful (discriminability) and natural (identifiability). This theory is tested by creating two manipulations. Firstly, multiplication of the chroma values of each pixel with a constant in the CIELab color space, i.e., chroma manipulation, is expected to increase only the usefulness by increasing the distances between the individual color points, enhancing the contrast. Secondly, introducing stereoscopic depth by varying the screen disparity, i.e., depth manipulation, is expected to increase both the usefulness and the naturalness. Twenty participants assessed perceived image quality, perceived naturalness and perceived depth of the manipulated versions of two natural scenes. The results revealed a small, yet significant shift between image quality and naturalness as a function of the chroma manipulation. In line with previous research, preference in quality was shifted to higher chroma values in comparison to preference in naturalness. Introducing depth enhanced the naturalness scores, however, in contrast to our expectations, not the image quality scores. It is argued that image quality is not sufficient to evaluate the full experience of 3D. Image quality appears to be only one of the attributes underlying the naturalness of stereoscopic images.

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Influence of chroma variations on naturalness and image quality of stereoscopic images

Kuijsters

IJsselsteijn

Lambooij

et al. 2009

Human Vision and Electronic Imaging XIV

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show abstract

“…Moreover, relatively brighter and more saturated colors are preferred by human vision (Camgö et al, 2002;Fedorovskaya, et al, 1997;Tangkijviwat et al, 2010). Based on study results, purple and yellow roses may not be presented appropriately under 3500 K lamps.…”

Section: Discussionmentioning

confidence: 94%

Changes in Perceived Colors of Cut Roses under Florist Shop Lighting

Yang¹,

Kang²,

Kim³

et al. 2013

J. Japan. Soc. Hort. Sci.

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“…Generally, researchers use statistical parameters i.e mean, standard deviation etc. to compute appearance attributes of whole images 20,21,22 .…”

Section: "Colour Strength" Frameworkmentioning

confidence: 99%

<title>Colour appearance descriptors for image browsing and retrieval</title>

Othman

Martinez

2008

SPIE Proceedings

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In this paper, we focus on the development of whole-scene colour appearance descriptors for classification to be used in browsing applications. The descriptors can classify a whole-scene image into various categories of semantically-based colour appearance. Colour appearance is an important feature and has been extensively used in image-analysis, retrieval and classification. By using pre-existing global CIELAB colour histograms, firstly, we try to develop metrics for wholescene colour appearance: "colour strength", "high/low lightness" and "multicoloured". Secondly we propose methods using these metrics either alone or combined to classify whole-scene images into five categories of appearance: strong, pastel, dark, pale and multicoloured. Experiments show positive results and that the global colour histogram is actually useful and can be used for whole-scene colour appearance classification. We have also conducted a small-scale human evaluation test on whole-scene colour appearance. The results show, with suitable threshold settings, the proposed methods can describe the whole-scene colour appearance of images close to human classification. The descriptors were tested on thousands of images from various scenes: paintings, natural scenes, objects, photographs and documents. The colour appearance classifications are being integrated into an image browsing system which allows them to also be used to refine browsing.

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Chroma variations and perceived quality of color images of natural scenes

Cited by 100 publications

References 3 publications

Influence of chroma variations on naturalness and image quality of stereoscopic images

Influence of chroma variations on naturalness and image quality of stereoscopic images

Changes in Perceived Colors of Cut Roses under Florist Shop Lighting

<title>Colour appearance descriptors for image browsing and retrieval</title>

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