伍瑞隆詩選

  夜讀書,見嶺南先人伍瑞隆題詩,字體法度精嚴之中,瀟灑秀逸,遒麗豐腴,有晉二王之風。故特尋其生平事蹟,偶見他處錄其詩若干首,以爲妙,咸集之於斯。

  伍瑞隆,字國開,一字鐵山。明末香山人。因結廬於鳩、艾二山之間,故自號鳩艾山人。

自題墨牡丹
睡起簾前曉日紅,名花開遍洛城東。
幽人碾墨傳清艷,只在踈踈幾筆中。
按:尾聯倒數第二字因詩軸年久似損壞而字跡不清,存疑。

初秋送弟有開兒昌年還玉溪兼柬劉衍崖舅氏
老舅亦已老,去年七十時。
賞花棋百局,留客酒千卮。
一別冬還夏,雙魚遠複遲。
天涯送兒弟,相憶淚如絲。

贈劉良倩
詞場俠少年,誰在劉生前。
傲骨世不賞,清才吾獨憐。
松為稽子韻,蘭是楚人編。
終令乘風起,名高日月邊。

祝棲老和尚七十有一
我歲乙酉夏,師年丙戌春。
所爭九個月,同作七旬人。
老宦曾何補,名僧自有真。
鼎湖山月白,為照劫灰塵。

依韻答胡明府絹庵
重陽風雨不成秋,官署山城一樣愁。
載酒未辭籬畔菊,題詩空上水邊樓。
邀歡豈必期來歲,卜醉還應續舊遊。
寄語江東張季子,好留清興在三洲。

答程周量
香風吹動筆花新,羨爾當今第一人。
慧鏡自天懸似日,文泉隨地出如神。
遭逢偶處還非偶,鑒別真時卻未真。
世事但存知己在,未須懷寶泣孤臣。

荔園座上贈諸子
楊柳新寒水面風,吹花送酒畫筵紅。
芙蓉洗出青天上,薜荔晴分碧霞中。
四海莫悲坭畔絮,萬家愁聽澤邊鴻。
詩成寫向相思樹,聊與君期紫極宮。

客岡州送棲壑和尚還鼎湖
昔人從師斷二愚,別來原只在須臾。
肉身喜見生菩薩,法座前稱老腐儒。
滿月一簾天在水,香風萬里露中珠。
憑師試展琉璃臂,入我岡州立雪圖。

即 事
(一)
黃梁一陣曉來風,龍眼吹殘橄欖空。
閒步長洲訪春色,西河無數落花紅。

(二)
河塘簇簇白藤花,岡尾岡頭十萬家。
見話橫江人不渡,峭帆風緊桂洲斜。

(三)
西頭南尾盡煙波,綠玉城中幽恨多。
林步酒家休得醉,寨前芳草奈愁何。

(四)
沙塘秋好發紅蓮,倚劍峰頭盡日眠。
下巷騎牛歸上巷,水邊沽酒過山邊。

(五)
秋風高隴不堪愁,雙美橋中廣渡頭。
鳳嶺駝山都莫問,更誰六社問瀛洲。

(六)
石橋坑下水流澌,烈女祠前花萬枝。
借問鳳凰山下月,至今猶照白蓮池。

(七)
何人移棹過江門,白石黃連尚有村。
閒步海洲懷古處,道娘無墓可招魂。

鳩艾山賦
(一)
雨痕初過綠生坭,睡起西窗意欲迷。
—樹紫微風盡落,亂紅堆地午鶯啼。

(二)
各花爭報各城秋,各色花光盡入樓。
感謝西風遠來意,早傳新爽到心頭。

(三)
誰教蝴蝶上花枝,花自多情學蝶飛。
我向北窗眠一覺,與花同作蝶飛歸。

(四)
紅蓼花開紅蓼沙,偶然移種入窗紗。
秋風未到花先到,想到秋來花又花。

(五)
獨岸亭亭秋海棠,秋來猶未見紅妝。
藕泉泉水芳如酒,為灌花魂作意香。

(六)
憑誰招得百花魂,毒霧連天草木昏。
獨有摩霄幾群鶴,月明清唳到山門。

(七)
一聲一聲飛上天,天邊佳氣碧如煙。
憑君說盡人間事,有客勞歌夜未眠。

(八)
山城無力養春風,春盡群花在夢中。
好逐鶴聲齊喚起,滿城香豔入新叢。

(九)
小小金魚五色鱗,往來無定為憐春。
池邊倒有千花影,魚亦隨花巧伴人。

(十)
山後山前五色禽,飛鳴處處是同心。
並頭花上連枝樹,一隊飛來一隊尋。

(十一)
春草無端五色花,佳人醉處日將斜。
殷勤撲上雙金鳳,一路憑君帶到家。

(十二)
嶺外寒輕節每遲,茲花九月早盈枝。
思君便得君來賞,一盞新醪一首詩。

(十三)
一自移居雩樂園,種花惟有菊花存。
西風不赴登高節,留待君來照綠尊。

(十四)
籬邊花草亦知愁,十月才開九月秋。
莫待深言此中事,餐英聊上白蘋洲。

開元寺試泉
片雲依絕磵,一水眄秋陽。
寄語神仙客,梅花遜不香。

竹枝詞
(一)
蝴蝶花開蝴蝶飛,鷓鴣草長鷓鴣啼。
庭前獨有相思樹,落盡相思人未歸。

(二)
妾愁那似比君愁,妾欲留君君不留。
君去桃花潭水上,有人來往送蘭舟。
(三)
楊柳千條與萬條,繫君蘭舸莫乘潮。
君心那似楊花亂,才逐風飄雨又飄。

(四)
紅霞映水月如煙,堤上行人駐馬鞭。
我唱鷓鴣君不信,君看江水一枝蓮。

(五)
閒情日日踏堤行,綠水紅霞繞樹明。
何處愁心最關切?夕陽鶯語一聲聲。

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伍瑞隆詩選

Further to My Previous Blog, rgd RVSF

I got in touch with Dr. Nalin Samarasinha at PSI, who wrote the codes for all of the special cometary processing filters at PSI website. He has beeing patiently answering every of my questions so I now can understand what his RVSF code is basically doing, though I know very little of FORTRAN. The discrepancy I spot between the source code and the explanation file is indeed a typo.

I added a new keyword to my IDL routine so that the user could have the option whether they like to switch on or off the function of sub-pixel sampling of the image prior to the function of the filter or not. Through some simple tests I realized that the differences between sub-pixelization and non-sub-pixelization of the image would not be very obvious in terms of visual inspection. However, the speed matters considerably, especially when the input image size or the part of regions selected is quite large — the processing time, in this case, could be quite consuming. So it’s a good idea to preview the enhanced image without sub-pixel sampling, not only would you save a great amount of time, but also this would give you a basic knowledge about if your kernel parameters are appropriate, and finally, to process the image by sub-pixelization with reasonable kernel parameters.

I couldn’t discern any difference in the enhanced images with or without sub-pixelization, however, a subtraction between the two clearly reveals what is previously hidden behind. See the following image.

The difference between non-sub-pixelization and sub-pixelization sampling. Linear stretch.
The difference between non-sub-pixelization and sub-pixelization sampling. Linear stretch.

Additionally, I’m very delighted to find that the resulting enhanced image processed by means of sub-pixelization shares great similarity with the one processed through Nalin’s code or PSI’s online tool. So I think my routine is quite successful.

At last, before the end of this update, I need to confess that I had mistakenly regarded the author of the source codes to be Padma Yanamandra-Fisher. I had been confused by their names, all look rather long for me… ><

Further to My Previous Blog, rgd RVSF

Testing My Radially Variable Spatial Filter Code

I think I need to update my blog; it has been so long since my last update… Also should I prove that I’m still alive here.

I saw a message in the comets-ml posted by Martino Nicolini that the PSI website has released a web tool for processing cometary images, including azimuthal median/average/renormalization filters, 1/rho coma model division, and, quite unfamiliar to me, radially variable spatial filter (http://www.psi.edu/research/cometimen). I attempted to process an image taken by HST regarding comet C/2012 S1 (ISON) in May 2013 with the online tool, however, I had difficulty in retrieving the enhanced or processed data. Weirdly the size of the to-be-downloaded file was always 0 KB, obviously problematic. With consideration that the network is not permanently available for me, it sounds absurd and waste-of-time for me to wait for accessible network before performing specially processed cometary images, and therefore I decided to write codes for my own purpose.

So I did by taking reference to the explanation file of the enhancement techniques, understanding the global idea of how the radially variable spatial filter works. Realizing the algorithm of the filter was proved easy, and it didn’t take me long to accomplish the IDL routine.

I did some tests with the image CometCIEF_test.fits provided in this page. The following was generated with kernel A = 4.0, B = 4.0, N = 0.4. It looks correct anyway, quite similar to the appearance in the tutorial file.

RVSF test imageHowever, I found my result would look somewhat different from those presented in the tutorial file if the kernel size was smaller — probably the scaling plays a role there, yet anyway my outcome would look less detailed. The corresponding FORTRAN source code of the filter in the PSI page seems to has a typo, which I have already reported to Padma Yanamandra-Fisher. I’m still comparing my codes against the PSI’s…

Testing My Radially Variable Spatial Filter Code